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About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. Key Responsibilities - Infrastructure & Platform Engineering : Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development : Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment : Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams What We're Looking For Required Experience 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences Key Attributes - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: Austin, Texas Compensation: $170,000-$270,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Benefits Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. Key Responsibilities - Infrastructure & Platform Engineering : Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development : Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment : Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams What We're Looking For Required Experience 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences Key Attributes - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: Dallas, TX Compensation: $170,000-$270,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Benefits Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. About the role Preferable to have someone near one of our offices in NYC or San Francisco, but open to hiring around the US for the right candidate. Join the frontier of shaping generative AI video and its legal landscape as an early lawyer at Runway wearing multiple hats. As AI Product & Partnerships Counsel, your mission is to enable the company to ship better products faster and accelerate product and data partnerships and other go-to-market deals. You are a self-starter who thrives at getting things done in fast-paced, unstructured environments. You have a passion for building scalable initiatives across our product and commercial legal workstreams. You will serve as a strategic partner to product, engineering, partnerships, sales, marketing, and the Runway Executive Team. Comfort working within a highly technical, rapidly evolving area of the law is a must. What you’ll do - Become a go-to advisor for product legal matters, from design to launch, by providing pragmatic, product-motivated advice - Accelerate AI product development and integrations by building playbooks and streamlining legal review of partnership deals, including data partnerships, IP and model licensing, procurement, reseller, and marketplace agreements - Accelerate AI product adoption by closing deals with Runway’s strategic partners and customers. These include B2B SaaS customer contracts for our generative AI SaaS platform and APIs, DPAs, and order forms. - Dive into the technical aspects of our generative AI products to learn them inside and out, to inform your advice to the business - Closely follow (and even shape) technical, legal, and policy developments in AI and translate them into practical product guidance - Implement practices allowing our legal team to scale our impact on the business, including enablement, self-serve resources, and AI-enabled automation What you’ll need - 6+ years of relevant experience, including in-house experience at a fast-paced technology company - Experience advising product development leaders and executives across a broad range of issues, especially IP and privacy - Experience closing partnership and go-to-market deals, such as data partnerships; IP and model licensing; robotics, hardware, and compute agreements; reseller; and other partner, customer, and vendor deals - Experience providing practical recommendations to senior leaders with limited time and information - Sound judgment in ambiguity: track record of gathering key information quickly and helping the business make smart decisions - Deep sense of ownership, whether you're advising our CEO on a novel legal issue or testing your new AI-enabled workflow for the nth time - Bias for action: why put something off if you can do it now? - Demonstrated interest in AI, creative tools or both - J.D. and admission in good standing with at least one state bar Nice to have - Generative AI models and agentic workflow understanding and interest - Experience closing strategic, IP-heavy partnerships - Experience in B2C and B2B industries and in product-led and enterprise businesses - Experience closing B2B SaaS customer deals - Big Law and/or hypergrowth tech startup experience Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. Working at Runway Great things come from great teams. We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator - GWM-1 - Gen-4.5 - General World Models - Robotics SDK - Conversational Real-time Agents - Runway Studios We're excited to be recognized as a best place to work: Crain's | InHerSight | BuiltIn NYC | INC

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is looking for Software Engineers to join the Memory & Search team. We own how Claude remembers you and how it finds what it needs, across Claude.ai, Cowork and Claude Code. That spans the user-facing experience (what Claude remembers, how people see and edit it, how search surfaces the right conversation) and the shared infrastructure underneath it, the memory service, indexing, retrieval and vector search. Memory is one of the biggest levers on whether Claude feels like it knows you. We recently moved memory from a periodically synthesized summary to a dynamic, editable, on-demand system, and then unified it so the same memory follows you across products. Search went from a top user complaint to something people rely on to find past work. The platform is now in place, and the next phase is finding the product form factors that make memory the most compelling and sticky part of using Claude. That is why we are hiring product engineers. The team is strong on infrastructure, and we want people who have shipped user-facing products at scale, have a sharp sense for what makes a product feel good, and have built agentic systems where the model, the tools and the user interface have to work together. You will run short, demo-driven experiments on top of the memory and search stack, decide what to keep based on real usage, and help the whole team think like a product team. If you have founded a company, been an early engineer at a startup, or taken a product from zero to one, you will recognize the way we want to work. This is a trust-sensitive surface. Memory touches privacy, consent and enterprise controls, so you will work closely with product, design, privacy, legal and safeguards, and you will be expected to treat those constraints as part of good product design rather than obstacles to it. Key responsibilities - Design, build and ship memory and search experiences in Claude.ai, Cowork and Claude Code, owning them end to end from the backend service through the model's tools to the user interface - Run product experiments on the memory and search stack: form a hypothesis, build a demo, put it in front of real users, measure, and make a clear persevere-or-pivot call - Shape how Claude uses memory and retrieval inside its agentic loop, including what the model stores, when it searches, how results are ranked and presented, and how the user stays in control - Define and track the metrics that tell us whether memory is actually making Claude more useful, and build the evaluations that keep quality honest as the system evolves - Improve search relevance and recall across conversations and memories, working across embeddings, hybrid retrieval and ranking as well as the interface that presents results - Partner with product, design, privacy, legal and safeguards to ship features that respect user consent and enterprise requirements such as customer-managed encryption keys and data retention policies - Raise the bar on product quality for the team through design reviews, code reviews and the standards you set for latency, polish and reliability Share the on-call for the systems you own Minimum qualifications - Experience building and operating user-facing products used by a large number of people, including the backend services behind them - Experience building agentic systems or LLM-powered products, including tool use, retrieval and prompt or context design - Strong programming skills in Python and TypeScript, with experience across backend services and web front ends - A track record of taking a product or feature from an idea to launch, and iterating on it based on usage data and user feedback - Experience defining product metrics and running experiments to make decisions - Strong product judgment: you notice when something feels off and you fix it, and you can explain why a design choice matters to users - Strong written and verbal communication, with experience working closely with product managers, designers and non-engineering partners - Interest in AI safety and Anthropic's mission Preferred qualifications - Experience as a founder, early-stage engineer, or someone who has taken a product from zero to one - Experience building search or retrieval systems: embeddings, vector search, hybrid lexical and semantic retrieval, or ranking - Experience building evaluations for LLM or ML systems, or measuring the quality of retrieval and ranking - Experience on consumer products with strong retention, or on personalization systems - Experience shipping features that handle sensitive data or meet enterprise requirements such as customer-managed encryption keys, data residency or HIPAA - Experience with latency-sensitive, performance-critical product work - Experience mentoring engineers or setting technical direction for a team The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI Security Architect, you will serve as Anthropic's trusted security expert for our most demanding enterprise customers. You'll engage directly with CISOs, security architects, compliance officers, and technical leaders at some of the largest healthcare and life sciences organizations to address their most critical questions about deploying Claude safely and securely. This is a pre-sales technical role focused on security, compliance, networking, and data architecture. Your job is to walk into a room full of security professionals and demonstrate deep expertise in enterprise security, regulatory compliance, and data protection. You'll help customers understand Claude's security architecture, data handling practices, and deployment options, and partner with them to design solutions that meet their specific regulatory and organizational requirements. You'll bring significant experience in enterprise security, cloud architecture, and technical pre-sales within regulated industries. Whether you've been a Security Architect, Solutions Architect, Field CTO, or senior pre-sales engineer at a cloud or security vendor, what matters is that you understand how large institutions evaluate and adopt technology, especially in healthcare and life sciences, and can speak credibly to their security and compliance concerns. We are looking for someone excited to help define how enterprises should think about security and compliance in the age of AI. How do MCP, autonomous agents, and RBAC work together? If working at the intersection of AI adoption and regulated industries excites you, this is the role for you. Responsibilities: - Serve as the primary security and compliance expert during customer engagements, addressing technical questions about Claude's architecture, data flows, encryption, access controls, and deployment models. - Partner with CISOs, security architects, and compliance teams at healthcare and life sciences organizations to understand their security requirements and design solutions that meet regulatory standards (HIPAA, GxP, HITECH, SOC 2, PCI-DSS, GDPR, federal mandates, etc) - Lead technical deep-dives on network architecture, data residency, API security, authentication/authorization, audit logging, and integration patterns for regulated environments. - Support enterprise security reviews, vendor assessments, and due diligence processes by providing detailed technical documentation and expert guidance. - Collaborate with GTM and Applied AI teams before and after customer engagements to align on strategy, prepare for security discussions, and ensure continuity from initial conversations through deployment. - Partner closely with Anthropic’s product and engineering teams to deeply understand Claude's security capabilities, provide real-time customer feedback on feature gaps and priorities, help assess technical feasibility of customer-specific security requirements, and influence roadmap priorities. - Develop and maintain security-focused collateral, reference architectures, and best practices documentation for regulated industries. - Lead enablement and create content for GTM and Applied AI Teams that helps them inform customers upstream about key security requirements and considerations. - Travel regularly to customer sites for security workshops, architecture reviews, and strategic account meetings. You may be a good fit if you have: - 8+ years of experience in enterprise security, cloud architecture, or technical pre-sales, with significant exposure to regulated industries (healthcare and life sciences). - Deep technical knowledge of enterprise security concepts: network security, identity and access management, encryption (at rest and in transit), API security, and audit/logging requirements. - Experience navigating compliance frameworks relevant to healthcare and life sciences organizations (HIPAA, GxP, HITECH, SOC 2, PCI-DSS, and GDPR). - A track record of engaging with CISOs, security teams, and compliance officers at large enterprises. - Strong understanding of cloud architecture and deployment models (AWS, Azure, GCP), including VPCs, private endpoints, and hybrid connectivity. - Excellent communication skills, including the ability to explain complex security topics clearly to both technical and non-technical audiences. - The ability to navigate ambiguity and move fast in a rapidly evolving market. - A collaborative mindset: sales at Anthropic is a team sport. - Excitement about AI's potential to transform highly regulated industries, and a genuine desire to help customers adopt it safely and responsibly. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $315,000 - $380,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Your work will change lives. Including your own. The Impact You’ll Make: Human biology stems from four billion years of evolution, which creates a proliferation of complexity and heterogeneity. The combinatorial explosion of biological hypotheses easily surpasses the number of atoms in the universe. Meanwhile, medical discovery advances at the snail pace of clinical trials, each taking years and costing over $100 million. As we enter the era of precision health and try to tailor treatments for each individual, continuing on today's discovery processes is clearly unsustainable. With the confluence of digital transformation and intelligence revolution, we have an unprecedented opportunity to develop a unifying biomedical world model by bridging virtual patient and virtual cell, and turning real-world data into a discovery engine to close the loop of clinical care and drug discovery. As a Principal AI Researcher, you will join our cross-functional team of top-notch scientists, engineers, and drug hunters in the quest of scalable biomedical discovery. You will work at the forefront of AI-powered drug discovery, advancing frontier research and end-to-end applications across discovery, design, and translation. The Team You’ll Join: Recursion is a pioneer in AI-native drug discovery. In the past decade, we have built an unparalleled array of infrastructures across drug discovery and clinical development, operating one of the largest AI compute clusters in biopharma, and spearheading industrial-scale phenomics for perturbation data generation at cellular resolution, long before "virtual cell" entered the mainstream. United under the mission of “decoding biology to radically improve lives”, we offer a unique vibrant environment that features frontier research, industrialized wet and dry labs, and real-world delivery, with close feedback loops and rapid iterations, much like a lean startup. You will join fellow experts across research and engineering, biology and medicine, business and operation, who are similarly committed to accelerating biomedical discovery and democratizing precision health for everyone in the globe. The Experience You Will Need: - PhD in ML, NLP, computer vision, or the equivalent practical experience - Passionate about real-world applications and impact - Strong verbal and writing communication skills - 10+ years of frontier AI research experience - Experience with large datasets and cross-functional AI projects - Experience in biomedicine and drug discovery a plus; willingness to learn a must! LI-DNI The Values We Hope You Share: - We act boldly with integrity. We are unconstrained in our thinking, take calculated risks, and push boundaries, but never at the expense of ethics, science, or trust. - We care deeply and engage directly. Caring means holding a deep sense of responsibility and respect - showing up, speaking honestly, and taking action. - We learn actively and adapt rapidly. Progress comes from doing. We experiment, test, and refine, embracing iteration over perfection. - We move with urgency because patients are waiting. Speed isn’t about rushing but about moving the needle every day. - We take ownership and accountability. Through ownership and accountability, we enable trust and autonomy—leaders take accountability for decisive action, and teams own outcomes together. - We are One Recursion. True cross-functional collaboration is about trust, clarity, humility, and impact. Through sharing, we can be greater than the sum of our individual capabilities. Our values underpin the employee experience at Recursion. They are the character and personality of the company demonstrated through how we communicate, support one another, spend our time, make decisions, and celebrate collectively. More About Recursion Recursion (NASDAQ: RXRX) is a clinical-stage TechBio company decoding biology to radically improve lives. Recursion is advancing a portfolio of differentiated investigational medicines across its wholly owned and partnered pipeline in oncology, rare disease, neuroscience, immunology, and other therapeutic areas with significant unmet need. Enabling its mission is the Recursion OS, an AI-native, end-to-end drug discovery and development platform integrating biology, chemistry, and clinical development into a unified intelligence system. Powered by proprietary multimodal data, purpose-built AI models, and bilingual teams fluent in both science and AI, the Recursion OS is designed to translate complex science into medicines that matter — faster, better, and at scale — for patients who are waiting. Recursion’s platform infrastructure is anchored in Salt Lake City, Utah and Milton Park, Oxfordshire, where its automated biology and chemistry laboratories generate proprietary data at industrial scale. Recursion also maintains offices in New York, Montréal, and London, three global hubs for talent and leadership at the intersection of AI and scientific innovation. Learn more at www.recursion.com , or connect on X and LinkedIn . Recursion is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected under applicable federal, state, local, or provincial human rights legislation. Accommodations are available on request for candidates taking part in all aspects of the selection process. Recursion leverages AI in our hiring process. We use Greenhouse's Talent Matching AI technology feature to help review applications against the skills and experience we've identified as important for this role. It analyzes your resume and application responses to assess how closely your qualifications match our criteria - but all decisions are made by our human recruiters and hiring managers, including whether to move to the next phase of review. Talent Matching does not automatically advance or reject any candidate. By submitting your application, you acknowledge that you have been informed about and consent to this use of the Talent Matching tool in our review process. Please refer to our Recursion Privacy Policy at https://www.recursion.com/privacy-notice/ for more information about our processing of personal data and your rights. Recruitment & Staffing Agencies: Recursion Pharmaceuticals and its affiliate companies do not accept resumes from any source other than candidates. The submission of resumes by recruitment or staffing agencies to Recursion or its employees is strictly prohibited unless contacted directly by Recursion’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Recursion, and Recursion will not owe any referral or other fees. Our team will communicate directly with candidates who are not represented by an agent or intermediary unless otherwise agreed to prior to interviewing for the job.

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We’re seeking an experienced Engineering Program Manager to join Cohere’s customer-facing Engineering Program Management team. We need someone with curiosity, drive, independence, and leadership, who has hands-on experience working directly with customers and managing projects for enterprise-grade software or enterprise-focused machine learning solutions. In return, you’ll have the unique opportunity to shape Cohere’s operations, collaborate with leading minds in the LLM space, work directly with our Strategic Customers as well as Applied ML (AML) Engineering, Forward Deployed Engineering (FDE), Platform , Product and Go-to-Market teams, and be the “technical” voice of Cohere for the customer. You will get a chance to create extremely high-impact contributions to our fast-growing company, product and culture. Please Note: This role is open to candidates based in [Dammam] As an Engineering Program Manager/ Technical Program Manager, you will: - Communicate: Provide clear, timely, and objective communication across the tech organization, Cohere teams, leadership, and most importantly - our strategic customers and external partners. - Optimize: Break down complex issues into strategies, driving engineering alignment with product, business, and marketing while fostering collaboration. - Plan: Create and manage program/project schedules, identify dependencies, manage risks, and drive organizational alignment. - Execute: Ensure on-time delivery, identify development needs, and establish checkpoints for status updates. - Problem solve: Proactively identify and resolve issues, coordinate cross-functional dependencies, and prioritize impacts to schedule and product quality. You may be a good fit if: - You have at least 5 years of experience as an Engineering or Technical Program Manager, with at least 3 years in customer-facing technical delivery and operations focused on enterprise-grade AI software/solutions - Knowledge or experience with LLM training or optimization would be a key differentiator - You are problem-focused and making customers successful really excites you - You are detail-oriented and extremely self-organized. You love enabling people and teams around you, and are excellent at capturing detailed notes/action items during highly technical meetings and tracking progress. - You have a Bias for Action - you are very execution focused and you like getting things done. - You have experience working with cross-functional teams to get technical products, services or solutions shipped to an internal or an external customer and can independently own tracking and reporting across multiple work-streams, with owners in different time-zones. - You are comfortable holding leaders and individual contributors accountable. You can be assertive while remaining diplomatic. You are not afraid to follow up with people to ensure shipping within committed deadlines. Full-Time Employees at Cohere enjoy these Perks: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. How and Where We Work: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form , and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers page.

About the Team The Applied AI Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and startups. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to late-stage startups. About the Role We are seeking a technically proficient, business-minded Applied AI Engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, guiding them through ideation, development, delivery, and scaling to accelerate and maximize the value of what they build on our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner in collecting and delivering high-fidelity product and model feedback internally. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Startups Applied AI Lead. This role is based in our Singapore office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Partner closely with strategic startup customers as their technical thought partner to build novel applications on our API, helping them rapidly move from ideation to scale. - Provide proactive guidance to maximize business impact and accelerate application development. - Experiment and prototype alongside customers, demonstrating practical use cases. - Contribute to open-source resources and scale the function by sharing knowledge, codifying best practices, and publishing useful resources. - Synthesize and deliver valuable feedback to the Product and Research teams. - Build relationships within the startup ecosystem, serving as a technical partner to both individual customers and the broader community. - Partner with the Sales team across startup accounts to identify customer opportunities, align technical work with business goals, and help customers bring AI applications to production. You might thrive in this role if you: - Have ability to speak Mandarin is a requirement as you will be working with Mandarin-speaking customers and/or vendors in the role. - Have 5+ years of experience as a software engineer, ML engineer or equivalent, ideally in a startup environment; experience as a founder or founding engineer is highly valued. - Have passion for startups and a belief in their potential to become future large enterprises. - Are proficient in Python, JavaScript, and a strong grasp of AI/LLM best practices. - Built and/or delivered prototypes on top of our API platform. - Can proactively identify opportunities for maximizing our customers’ business value through leveraging the OpenAI API. - Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done. - Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. - Are an effective, high throughput operator who can drive multiple concurrent projects and prioritize ruthlessly. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why the Cohere TPM role? As our Generative Machine Learning organization has continued growing, we are looking for more Technical Program Managers to join the team! At Cohere, TPMs are pivotal to our success, being seen as operational experts specializing in cross-functional efforts. Great TPMs at Cohere are well-rounded, executing with precision at the tactical level, while partnering with senior leaders and shaping the big picture at a strategic level, and the opportunities are endless in growing the scale and impact of their work. Cohere’s TPMs would often be described as organized, execution-oriented, pragmatic leaders who are adaptable to the needs of the company and the programs they lead. As a reward for the depth and breadth of expertize that you bring to the table, you will get to work alongside some of the most talented AI researchers and industry experts in the world on building cutting edge AI technology. No day will be the same as the one before, and the dynamic high growth environment will be absolutely perfect for anyone excited about solving novel problems, bringing structure to oftentimes chaotic and fast-paced environments, and ambitious about scaling their own impact and growth alongside the company! Please note: While we are remote-first and accept candidates from all over the world, we are highly prioritizing hiring for people who are within 1-2 hours of British Standard Time (BST). As a Machine Learning Technical Program Manager, you will: - Establish, improve, and scale foundational processes that allow the Generative Modeling teams to execute better, faster, and more predictably - Scale the operational capacity and effectiveness of the Modeling TPM team in collaboration with the Modeling TPM lead to ensure the function can remain lean and effective during a period of the program portfolio complexity and size continuing to rapidly increase - Flexibly adapt to the needs of the company, programs, and the team from tackling long-horizon programs that can span quarters or even years to jumping onto often highly ambiguous short-term challenges that can have company-wide impact - Partner directly with leaders within and outside of the Modeling organization on efforts to design, train and improve our core generative models - Lead cross-functional, oftentimes company-wide programs and strategic initiatives, collaborating and coordinating with cross-functional teams such as Product, Engineering, Legal, Platform, Infra, Policy, and Finance - Operate as an organizational expert in improving engineering execution rigor and operations on the ground, while contributing to the strategic layer in areas such as long-term strategic planning with senior modeling leadership - Map out dependencies and risks, and ensure that cross-functional execution across the program runs smoothly, communicating status with non-technical and technical stakeholders and senior management - Both own and enable a useful communication flow of priorities, ideas, and knowledge throughout and beyond the Modeling organization in line with your programs - Respond quickly to program-level changes, clarifying new scope, and managing resource needs in response to evolving priorities You may be a good fit if you have: - 5-10 years as a Technical Program Manager AND 5+ years of experience working directly on AI/ML. Strong preference for candidates that have worked directly in building foundation models. - In-depth knowledge of machine learning, particularly when it comes to Natural Language Processing & Large Language Models (LLMs). Bonus points for experience with Multimodal AI. - Experience with working in a chaotic, fast paced, low structure environment. We need someone who is pragmatic, can roll up their sleeves when needed, and can function at the tactical and strategic level to do whatever it takes to make Cohere’s models succeed - Personal hands-on understanding of the unique challenges of managing projects and programs in the AI/ML development space as opposed to traditional software program management - Managed projects & programs requiring a strong general business acumen, such as coordinating with Finance on reporting needs or Policy on regulatory compliance matters — the broader your experience beyond ML technical program management, the better! - (optional, but preferred) Have technical experience in a hands-on capacity. We don’t necessarily need someone with hands on experience training models, but you need to feel comfortable sitting in the same rooms with some of the best researchers in the world, working on highly complex, cutting edge ML problems If some of the above - other than the ML TPM experience - doesn’t line up perfectly with your experience, we still encourage you to apply! If you consider yourself a thoughtful worker, a lifelong learner, and a kind and playful team member, Cohere is the place for you. We welcome applicants of all kinds and are committed to providing both an equal opportunity process and work environment. We value and celebrate diversity and strive to create an inclusive work environment for all. Full-Time Employees at Cohere enjoy these Perks: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. How and Where We Work: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form , and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers page.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As part of our growing Data Science and Analytics team, you will play an instrumental role in our company's mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You bring experience from high-bar teams and are eager to help shape the norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world. You'll be the senior data science leader for Model Experience and a strategic thought partner to product, engineering, and research leaders. Working where frontier AI research reaches the public, you'll help shape model roadmap and launch decisions, bringing a point of view on how users experience our models and what good looks like beyond benchmark scores. As a tech lead manager, you'll also hire and manage a team of data scientists, setting their agenda, personally leading the highest-stakes analyses, and raising the bar for how data shapes model and product decisions. Responsibilities: - Act as a strategic thought partner to product, engineering, and research leaders, helping shape model roadmap priorities, launch decisions, and the major bets the team makes - Set the data science agenda for Model Experience, deciding where the team can have the most impact on model development and launch decisions and what it should deprioritize - Hire, manage, and develop a team of data scientists, coaching them to move from answering questions to shaping decisions - Frame the most important and ambiguous questions about model quality and user experience, size the opportunities, and make clear recommendations, including when they challenge the current direction - Define how Model Experience measures success, establishing the core metrics and measurement frameworks across external products and internal testing that align teams and leadership on what matters - Set the standard for experimentation and causal inference across Model Experience, including where launches lack a clean A/B test, and personally lead the highest-stakes analyses - Turn complex analyses of model and user behavior into clear narratives and recommendations that drive decisions with senior leadership and cross-functional partners - Establish foundational data practices and shape the analytics infrastructure Model Experience needs to support rapid iteration and decision-making as our models and products evolve You may be a good fit if you: - Have extensive experience in data science, including leading analytics for a product or research area at significant scale - Have 3+ years managing data science teams, including setting team direction, hiring, and developing senior data scientists - Have been a trusted partner to senior product, research, and business leaders, with clear examples of changing a roadmap or high-stakes decision - Bring strong product sense and business judgment, including the ability to frame the right question and take a position with incomplete information - Have deep expertise in experimental design, causal inference, and statistical modeling at high scale, with enough fluency in Python and SQL to stay hands-on and guide others' technical work - Communicate clearly in writing and in presentations, including to executive audiences - Have a bias for action and thrive in ambiguous, fast-moving environments where you must create clarity and drive progress - Care about the company's mission of building helpful, honest, and harmless AI - Strong candidates may also have: - Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem - Experience as a tech lead manager or player-coach, balancing hands-on technical work with people management - Experience building or scaling a data science team in a fast-growing organization - Experience working closely with Product or Research teams, especially on LLM or AI products - Comfort working with unstructured data The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $380,000 - $460,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Inference organization serves Claude to millions of users and enterprise customers, across our own products and the world’s largest cloud platforms, with the speed, reliability, and efficiency that frontier AI demands. The stack that makes this possible is deep and tightly coupled: accelerator kernels, an in-house inference engine that manages the entire token path for both production and research workloads, distributed routing, autoscaling, and capacity management. Every layer affects the others, often in ways that are hard to see in isolation. We build across GPUs, TPUs, and Trainium, and the complexity of building, testing, and shipping inference software grows with every platform we add. We're looking for a Technical Program Manager to drive the programs that scale it. The work spans four closely coupled areas: - Scaling and infrastructure. Routing, autoscaling, and capacity management for the serving fleet, and bringing new capacity online. - Velocity. The toolchains, development environments, and CI/CD that let inference engineers build, test, and ship across every accelerator platform. - Inference engine. The software between the accelerator kernels and the routing layer that serves every request. - Performance. Improving throughput, latency, cost, and reliability across the stack, with correctness treated as part of performance. This is not a status-tracking role. You'll own outcomes end to end, often where no single team is accountable for the whole picture. Much of your value comes from crossing boundaries into Research, Safeguards, Security, Compute, Infrastructure, API, and our cloud and silicon partners, and bringing back the requirements and dependencies that no team sees from inside its own space. There is little process to inherit, and we want to keep it that way: you'll build the minimum machinery the work needs and remove it when it stops helping. And because this is Anthropic, you'll have Claude as a collaborator. We expect TPMs on this team to push hard on what AI-assisted program management and fleet operations can look like. Key responsibilities - Own the programs that scale Claude’s serving fleet across accelerator and cloud platforms, from early direction through delivery. - Drive new capacity online end to end, working across compute, infrastructure, security, networking, and inference teams so one person is accountable for the whole path. - Build visibility into supply, demand, and utilization with capacity and finance partners, and drive trade-offs among utilization, cost, latency, and reliability to a clear decision. - Lead reliability programs and large migrations without disrupting production traffic or research, and make sure incident follow-ups land in team roadmaps. - Drive the programs that make inference engineers faster: define the productivity metrics that matter, find the bottlenecks, and improve how software is built, tested, and released across platforms, in step with Anthropic’s central Infrastructure org. - Coordinate roadmaps and priorities across the production, research, and safeguards needs that depend on the same teams. - Track performance and efficiency work from opportunity to measured impact in production, with correctness held as a release criterion. - Own inference readiness for model launches alongside our launch TPMs. Minimum qualifications - 7+ years of experience as a TPM, or in an equivalent engineering or SRE lead role, owning large multi-team infrastructure programs end to end in production distributed systems, ML infrastructure, or cloud platforms. You can speak to the outcomes in detail, including where a program slipped and what you did about it. - Technical fluency in large-scale serving infrastructure, including request routing and load balancing, autoscaling, capacity planning, cluster orchestration, deployment and rollout, and observability. You know enough to challenge a design, find the real risk, and add value beyond tracking. - A working understanding of how LLM inference uses hardware (prefill and decode, batching, caching, compute versus memory bandwidth versus interconnect), or a track record of getting deep in an unfamiliar technical domain quickly. - A track record of building program mechanisms from scratch on ambiguous, fast-moving efforts, and of retiring process that has stopped earning its keep. - The ability to drive outcomes across organizations you don't manage, with competing priorities and unclear decision ownership. You read people and rooms well, know when to push and when to listen, and earn the trust of senior engineers and researchers. - Strong written communication, including plans, reviews, and executive updates that many teams depend on. - Low ego and high ownership. You do whatever the program needs, whether that is writing a script, running an incident bridge, or chasing a quota, and you care more about the outcome than about scope or credit. - Care about Anthropic's mission and about serving frontier AI safely and reliably. Preferred qualifications - Direct experience with LLM or ML inference serving at scale, such as model servers, batching and scheduling, KV caching, quantization, speculative decoding, or multi-model routing. - Experience with accelerator infrastructure (GPU, TPU, or Trainium), including cluster bring-up, hardware qualification, or running one workload across more than one accelerator platform. - Experience managing capacity across multiple clouds or regions, including demand forecasting, headroom policy, cost modeling, or unit economics for compute-heavy services. - Experience with developer productivity, release engineering, or CI/CD at scale, especially for hardware-dependent workloads, and with using engineering metrics to measurably raise velocity. - Experience running performance or efficiency programs, with enough grounding in rooflines, kernels, ML compilers (XLA, Triton, Neuron), numerics, or collective communication to reason about trade-offs with the engineers doing the work. - Familiarity with Kubernetes-based orchestration and job scheduling. - Experience working with research teams and turning their needs into infrastructure requirements. - Practical experience using AI tools in your own workflow, including building automations or agents, and clear ideas about where they help and where they don't. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $290,000 - $435,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role: We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. What You'll Do: - Infrastructure & Platform Engineering : Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development : Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment : Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams What You'll Bring: 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect, Deployed Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences Key Attributes: - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience Compensation: €110,000-€185,000 base salary + equity Location: - Netherlands, Amsterdam - Remote with up to 25% travel Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Benefits Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

At Scale , our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's Machine Learning Research team builds the foundation for the next generation of AI systems — pushing the boundaries of what's possible with frontier models while ensuring safety, reliability, and alignment at every step. Our work spans generative AI, reinforcement learning and advanced post-training methods, scalable oversight, synthetic data pipelines, red teaming, and evaluation science. We are developing a large-scale hybrid human-machine system to power machine learning pipelines for dozens of industry-leading customers. These models and systems form the backbone of Scale's long-term strategy, enabling billions of tasks monthly and supporting some of the most complex and advanced use cases in the AI ecosystem. As an intern, you'll work on a combination of deeply technical ML applications in production and cutting-edge research problems, with mentorship from world-class researchers and the opportunity to collaborate with leading teams across industry and academia. Interns own real, published or shipped work — not side projects. Example Projects - Measure the dangerous capabilities of frontier models and conduct preparedness research - Research the science and creation of new benchmarks for frontier models - Develop new methods for training models to excel on extremely difficult reasoning problems that require long chains of thought - Research reinforcement learning and post-training methods that improve model reliability on high-stakes tasks - Research scalable oversight protocols that enable humans to produce and quality control reasoning chains beyond their native capabilities - Study the boundaries of model generalization and capabilities to inform data-driven advancements - Research synthetic and hybrid data with humans in the loop to scale up high-quality data generation - Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics - Create post-training or agentic solutions that integrate into our ability to deliver applications for enterprise and public sector clients Required to Have - Currently enrolled in a BS, MS or PhD program with a focus on Machine Learning, Deep Learning, or Natural Language Processing, with a graduation date in Fall 2027 or Spring 2028 - Available for a Summer 2027 internship (May/June start dates) in San Francisco Or New York. - Prior research experience or a track record of publications on LLMs, NLP, multimodal models, agents, safety, evaluation, alignment, or a related field - Experience with one or more general purpose programming languages, including Python, Javascript, or similar Ideally You'd Have - A previous internship in Machine Learning, Deep Learning, Natural Language Processing, Adversarial Robustness, Alignment, Evaluation, or Agents - Experience as a researcher — through internships, full-time roles, or at a lab - Publications at top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP or AAAI, or contributions to open source projects - Hands-on experience with reinforcement learning, agentic systems, or evaluation infrastructure How We Work Our credos shape how we make decisions and work as a team: - Earn Customer Love — trust is earned with every interaction, every delivery, and every problem we solve - Team Flow — ideas, energy, and support move freely across teams; optimize for the whole - Quality is Our Cheat Code — the systems that deliver quality consistently are a structural advantage - Find the 20% — find the inputs that drive the outcomes and execute them completely - Write the Market — our research puts us at the frontier, and we bring our partners there first - Three Moves Ahead — consider the consequences of consequences, and plan accordingly Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco and New York is: $120,000 - $150,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

About the Role We're looking for a software engineer, reliability-minded but still a builder, to own what happens in production to the Kubernetes-native control plane that provisions and runs our GPU inference fleet. The platform team builds the manifest-driven API and controllers that let the inference team declare what they need, a cluster, a model deployment, a capacity change, and get it reconciled underneath. Your job is to keep that promise true in the real world: triaging InfiniBand issues when prefill and decode nodes stall exchanging KV cache over RDMA, diagnosing hero-model and LoRA-serving faults that don't show up in generic health checks, and extending the automated self-healing system so each new failure mode becomes a permanent fix instead of a recurring page. The core value we're after is keeping the decoupling real even when things break, and keeping the fleet efficient without that efficiency becoming a new source of instability. You'll own SLOs and error budgets for inference serving, lead incident response, and turn what postmortems teach you into actual changes in the controllers and automation, not just updated runbooks. You'll also work the reliability side of capacity efficiency, since a mistuned defragmentation or bin-packing pass is itself a production risk. Strong candidates have hands-on production-reliability experience on large-scale distributed or GPU-serving systems, are comfortable troubleshooting InfiniBand/RDMA and Kubernetes controller/CRD-based platforms, and think about GPU infrastructure, and the tools that keep it reliable, as software to be engineered. A product mindset applies: the on-call experience, the clarity of an alert, and the judgment built into an automated remediation are things you ship and iterate on. Responsibilities - Operate the provisioning state machine in production: own the health of the host lifecycle pipeline, discovery, inference bring-up, GPU driver/CUDA validation, health checks, decommission/RMA, triaging stuck or failed state transitions at fleet scale and feeding real failure patterns back into how the states and transitions are designed. - Triage and extend automated self-healing: when the node-scanning and remediation platform misses something, a new failure mode, an InfiniBand issue in disaggregated prefill/decode serving, a GPU Xid variant, a hero-model or LoRA-specific fault, diagnose it live, drive the fix to production, and turn it into a new detection/remediation plugin so it's automatic the next time. - Own end-to-end reliability of the pipeline: hold the SLOs and error budgets for provisioning and fleet health, lead incident response when idempotency, retry, rollback, or drift assumptions break down in practice, and drive the systemic fix, not just the hotfix. - Partner with the inference/ML platform team from the production side: be the one who knows how real cluster topologies, interconnects, and scheduling constraints actually fail in the field, and feed those failure modes back as first-class requirements into the platform's abstractions. - Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production, enabling advanced research through awesome engineering. - Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. - Build tools to give us visibility into our bottlenecks and sources of instability, then design and implement solutions to address the highest-priority issues. - Lead reliability cross-functionally: build coalition across infra, ML platform, and product teams around shared reliability priorities, manage stakeholders through incidents and roadmap trade-offs, and represent the reliability point of view in planning so it shapes decisions before they ship, not after an outage. Requirements - Experience operating a provisioning or host-lifecycle pipeline in production, comfortable troubleshooting stuck or failed state transitions (discovery, bring-up, GPU driver/CUDA validation, health checks, decommission/RMA) at fleet scale, and translating real failure patterns back into improvements to the state machine’s design. - Deep experience owning production reliability for large-scale distributed systems; GPU/ML-serving infrastructure experience is a strong plus. - Hands-on experience troubleshooting InfiniBand/RDMA networking issues, ideally in a multi-node training or disaggregated-inference context — comfortable reading IB port counters and subnet manager logs, not just application metrics. - Familiarity with the operational realities of multi-tenant model serving (LoRA/adapter-based serving) and with running differentiated SLOs across model pools of different priority. - A demonstrated track record of eliminating operational toil through automation and tooling you built yourself, not just process or documentation. - Hands-on experience with Kubernetes controller/CRD patterns, reconciliation loops, and node-level health/remediation systems. - Comfort with event-driven architectures, backpressure/circuit-breaking design, and treating observability (metrics, logs, traces) as something built into a system, not added after an incident. - A software-engineering mindset first: you write and ship production code, and you think about GPU infrastructure as software to be engineered, not a fleet to be manually operated. About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Application Policy Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy .

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's legal team operates at the frontier of some of the most consequential legal and regulatory questions of our time — from landmark copyright matters to first-of-their-kind AI regulatory frameworks emerging across dozens of jurisdictions simultaneously. As we scale, the volume and complexity of our discovery and information governance obligations are growing rapidly. We are looking for a Discovery Technical Operations Specialist to join our Litigation and Regulatory team and help build out Anthropic's discovery operations from the ground up, support active matters, and help drive information governance maturation. This is a unique opportunity to be a part of a critical function at one of the most closely watched companies in the world. You will work hand-in-hand with our discovery leads, litigation and regulatory counsel, outside counsel, discovery vendors, and cross-functional partners such as Security and IT to manage retention, preservation, collection, and production of electronically stored information (ESI) across active matters. Beyond matter-level support and programmatic development of discovery systems and processes, you will also help execute the development of Anthropic's broader information governance program, including data classification standards and defensible disposal practices that keep pace with a rapidly scaling AI company's evolving data landscape. The right person for this role will be equal parts technical operator and operational project manager. Key responsibilities - Build and operate discovery operations across the full EDRM lifecycle (preservation, collection, processing, hosting, review, and production including for novel and AI-specific data types) - Support the operational design and execution of the legal hold program including custodian identification workflows, hold issuance and tracking, periodic re-notification, custodian acknowledgments, and defensible release - Support and improve the discovery technology stack including RelativityOne, in-place preservation and collection tooling across Slack, Google Workspace, and internal systems, and supporting analytics and review platforms including configuration, access controls, templates, and reusable workspaces - Partner with discovery team, in-house counsel, outside counsel, vendors, and internal technical teams; coordinate matter execution, status, and escalations - Partner with Security, IT, and product engineering to support Anthropic's data landscape, instrument new data sources for hold and collection, and ensure each ESI source has a governed retention, hold, and disposition path - Improve and support the operational layer of Anthropic's information governance program: retention schedule execution, classification rollout, defensible disposition workflows, and data-inventory maintenance in close partnership with the Discovery Lead and information governance stakeholders - Integrate AI and automation into the EDRM lifecycle: generative-AI-assisted review, advanced analytics, custom Relativity applications, and agentic workflow automation for intake, hold tracking, status reporting, and internal documentation - Support active litigation, government investigations, and regulatory inquiries as the operational counterpart on the matter team coordinating workstreams, managing vendor execution, and surfacing operational risk and cost trade-offs to counsel - Design and build internal tools to streamline and manage critical discovery workflows (legal holds, preservation, collection, ECA, and production), and develop dashboards that report on data management trends and cross-matter discovery status Minimum qualifications - Hands-on discovery experience across the full EDRM lifecycle, with demonstrated ownership of operations on complex matters in an in-house legal department, government agency, law firm, or vendor - A track record of supporting complex discovery operations functions - Working knowledge of major discovery platforms (Anthropic uses RelativityOne), including administration, search and analytics, AI/TAR workflows, custom application development, and AI workflows - Strong understanding of the Federal Rules on discovery and evidence, ESI preservation obligations, and proportionality, with the operational fluency to translate those obligations into workflows - Experience operating discovery across modern enterprise data sources Slack, Google Workspace, mobile, and engineering systems and an understanding of how to bring novel data sources under preservation and collection - Strong project management instincts and a track record of running multiple concurrent matters and programs under tight deadlines, with composure and precision - Demonstrated ability to communicate technical discovery and operational concepts clearly to attorneys, executives, engineers, and non-technical stakeholders Preferred qualifications - 6+ years of hands-on discovery experience across the full EDRM lifecycle - Experience standing up discovery operations at a young and/or fast-scaling company, particularly in the context of new kinds of ESI - Experience embedding with engineering or product teams to define discovery and information governance requirements, prioritize roadmap, and ship hold-capable and collection-capable features into core enterprise tools - Hands-on integration of generative AI and agentic workflows (e.g., Claude, Claude Code, or similar) into operational discovery work project tracking, status reporting, internal documentation, custom tooling, and script maintenance - Technical fluency working with engineering teams and modern infrastructure APIs, cloud (AWS, GCP), data pipelines, and version control and comfort writing, reading, or maintaining small scripts where useful - Experience operating information governance programs at scale including retention scheduling, data classification, defensible disposition, and data mapping across heterogeneous enterprise data sources - Experience with applying AI and automation to discovery operations, including generative AI for review, agentic automation, and operational tooling for hold tracking, reporting, and documentation - A collaborative, hands-on orientation, with integrity and genuine curiosity about building operational programs in a fast-moving environment The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $170,000 - $220,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You bring experience from high-bar teams and are eager to help shape the norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world. You’ll be the senior data science leader embedded in our Core Apps product team and a strategic thought partner to its product leads. You’ll help set product direction for Claude Code and other new bets across Core Apps: bringing a point of view on where to invest, how to grow our Apps business, and how to deliver more value for our users. As a tech lead manager, you’ll also manage a small team of Product Data Scientists, setting their agenda and raising the bar for how data shapes product decisions. Responsibilities: - Act as a strategic thought partner to Core Apps product leads, helping shape product strategy, roadmap priorities, and the major bets the team makes - Set the data science agenda for Core Apps, deciding where the Product Data Science team can have the most impact and what it should deprioritize - Manage and develop a small team of Product Data Scientists, coaching them to move from answering questions to shaping decisions - Frame the most important and ambiguous questions facing the business, size the opportunities, and make clear recommendations, including when they challenge the current direction - Define how Core Apps measures success, establishing the core metrics and measurement frameworks that align teams and leadership on what matters - Set the standard for experimentation and causal inference across Core Apps, and personally lead the highest-stakes analyses - Turn complex analyses into clear narratives and recommendations that drive decisions with senior leadership and cross-functional partners - Establish foundational data practices and shape the analytics infrastructure Core Apps needs to support rapid iteration and decision-making as our products grow You may be a good fit if you have: - Have extensive experience in data science, including leading analytics for a product area at significant scale Have 3+ years managing data science teams, including setting team direction and developing senior data scientists Have been a trusted partner to senior product and business leaders, with clear examples of changing a roadmap or high-stakes decision Bring strong product sense and business judgment, including the ability to frame the right question and take a position with incomplete information Have deep expertise in experimental design, causal inference, and statistical modeling at high scale, with enough fluency in Python and SQL to stay hands-on and guide others’ technical work Communicate clearly in writing and in presentations, including to executive audiences Have a bias for action and thrive in ambiguous, fast-moving environments where you must create clarity and drive progress Care about the company’s mission of building helpful, honest, and harmless AI - Strong candidates may also have: Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $460,000 - $460,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About the team The Applied AI Engineering team is responsible for ensuring the safe and effective deployment of generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our API customers, working to build an effective backlog of frontier AI use cases for their industry and drive them to production through strong technical guidance. As an Applied AI Engineer in the Digital Native segment, you’ll work with industry-leading technology companies like Stripe, Uber, and Reddit to bring new AI capabilities into the products their customers use every day. You’ll partner directly with experienced product and engineering teams to turn frontier model capabilities into new features and agentic experiences. The work combines rapid experimentation with the demands of established products: complex systems, real users, and high expectations for quality and performance. Lessons from these deployments inform OpenAI’s product and research teams. About the role You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact – not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in our São Paulo, Brazil office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Deeply embed with our most sophisticated and technical platform customers, serving as their technical thought partner in ideating and building novel applications on our API. - Forge relationships with CTOs, AI Product and engineering leaders to ensure their application’s successful deployment at scale. - Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. - Build targeted prototypes, pilots, and model evaluations with customer teams to test product ideas, guide architecture decisions, and inform their product roadmaps. - Collaborate with our Product and Research teams in validating upcoming frontier AI capabilities in customer environments, and deliver high-signal feedback to steer OpenAI’s roadmap. - Scale the Applied AI Engineer function through sharing knowledge and publishing best-practices to our internal and external repositories. - Evaluate emerging model capabilities, developer tools, and implementation patterns, and translate relevant advances into practical recommendations for customer applications. - Work alongside customer teams through on-site workshops and implementation sessions, helping resolve technical challenges and strengthen relationships. This includes occasional travel. You’ll thrive in this role if you: - Bring 8+ years of deep, hands-on technical experience and an eagerness to work closely with customers. Our team consists of former startup founders, software and ML engineers, technical product managers and solution architects. - Have a track record of personally leading complex, production-scale AI/ML systems from ambiguous discovery through production deployment, adoption, and measurable business impact. - Are passionate about being on the forefront of the latest AI industry trends, incl. agent architecture patterns, advanced prompt and context engineering, evaluation frameworks, safety, and security. - Are proficient in Python, JavaScript, TypeScript, or similar languages and are comfortable building production-quality prototypes and reference implementations. - Demonstrate strong technical judgment: know when to go deep personally, when to mobilize specialists, and how to make clear recommendations with incomplete information. - Have a humble attitude and an eagerness to help others with empathy. - Operate with high horsepower, are adept at frequent context switching and working on multiple projects at once with expansive ownership, and ruthlessly prioritize. - Thrive in dynamic environments and can navigate ambiguity with ease. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: As a Manager of Startups Applied AI Architects at Anthropic, you will drive adoption of frontier AI by leading a team of technical architects to help startups build AI-native products with the Claude Developer Platform. Your team is expected to win the trust of founders and engineers by supporting their technical ambitions from early product to scale. You'll bring your own builder credibility and startup instincts to the role — setting the vision for what great technical partnership looks like in the startup segment, developing a high-performing team, and personally carrying relationships with Anthropic's most strategic early-stage accounts. This is a role for a proven technical go-to-market leader who knows how to build teams that move at startup speed, earn the trust of deeply technical buyers, and turn a scrappy early engagement into a lasting technical partnership. You'll define the playbooks for nurturing and scaling new customers, set the bar for technical excellence, and grow the people — while staying close enough to the ground to know what's actually working. You will partner with sales leaders and work as one team to support your customers. Responsibilities: - Lead, develop, and grow a team of Startups Applied AI Architects — setting a high bar for technical credibility, customer impact, and startup-paced execution - Drive team performance through clear goal-setting, regular coaching, and a culture of continuous technical development - Personally lead pre-sales engagements with high-priority startup accounts, from initial technical discovery through deployment and expansion, modeling what great looks like for your team - Build and own the segment's technical playbooks: how to run technical evaluations, develop customer-specific eval frameworks, architect LLM solutions for resource-constrained early-stage teams, and win against competitive alternatives - Partner with aligned Account Executives and GTM leadership to shape segment strategy and drive Claude API adoption across the startup ecosystem - Ensure your team consistently surfaces insights on how startups are building with Claude — emerging use cases, deployment patterns, architectural decisions — and translate that signal into actionable feedback for Product and Engineering - Drive cross-functional influence across Sales, Product, and Engineering to advance startup customer needs and shape roadmap priorities - Build Anthropic's technical presence and credibility in the startup ecosystem through events, conferences, workshops, and content - Stay ahead of the AI engineering landscape — context engineering, eval frameworks, agentic architectures, developer tooling — and ensure your team is operating at the frontier You may be a good fit if you: - Have 8+ years of experience in technical customer-facing roles (Solutions Architect, Sales Engineer, Forward Deployed Engineer, or similar), with 5+ years leading and managing pre-sales or technical go-to-market teams - Have a strong track record of building and developing high-performing SA teams — you know how to hire well, coach effectively, and create an environment where technical talent grows and does their best work - Have deep experience working with startups or high-growth technology companies — you understand the velocity, constraints, and culture of early-stage companies and know how technical decisions get made at each stage of the journey - Bring genuine builder credibility: you've built and deployed LLM-powered applications, you speak the language of founders and founding engineers, and you can earn the trust of deeply technical audiences without relying on a title - Have hands-on expertise with context engineering, LLM evaluation frameworks, and modern AI architectures, and can guide both your team and customers through the decisions that separate a prototype from a production-grade system - Are comfortable with Python and fluent in the LLM frameworks, tools, and integration patterns common in startup engineering stacks - Are energized by building in ambiguous environments — you're excited to define the playbook, not just run it, and you thrive in fast-moving contexts where the technology and the customer segment are both evolving rapidly - Have a genuine passion for making powerful technology safe and societally beneficial Strong candidates may have: - Experience as a technical founder or in a founder-led sales motion, giving you firsthand understanding of what technical buyers in the startup world are actually evaluating - A track record of winning competitive technical evaluations against other LLM providers - Experience building foundational team infrastructure from the ground up: hiring frameworks, onboarding programs, technical playbooks, and coaching systems in a high-growth environment - Deep familiarity with how developer infrastructure procurement evolves from seed through Series B and beyond, and how to adapt your team's approach accordingly - A visible technical presence in the startup or AI engineering community through conference talks, written content, or open-source contributions The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $315,000 - $380,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Integrity and Authenticity Policy Manager, you will be responsible for developing, refining, and maintaining policies that prevent the misuse of AI systems for deception, manipulation, and unauthorized monitoring at scale. You will serve as the policy owner for risks related to inauthentic behavior, influence activity, surveillance, and the profiling of individuals and groups, and you will help shape policy frameworks across several areas, including authenticity, information integrity, and privacy and surveillance. Your initial focus will be on translating the Integrity and Authenticity risk framework into clear, enforceable policies, ensuring policy language addresses emerging threats identified by partner teams, and establishing guidelines that enable consistent enforcement decisions. Many of the most serious harms in this space begin with upstream steps that look routine on their own, such as compiling records about a person, automating account creation, or sorting users by inferred identity. Part of your work will be defining where those steps become prohibited. The role will expand as AI capabilities advance. Safety is core to our mission. You will help ensure our products cannot be used to deceive people at scale, monitor and profile people without their knowledge or consent, or sort and target populations based on sensitive characteristics. Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature, as well as detailed descriptions of privacy violations, surveillance abuses, and deceptive campaigns targeting vulnerable people. Key responsibilities - Develop and define policy boundaries for covert monitoring, tracking, and surveillance across different contexts, drawing the distinction between malicious behaviors and compliant dual-use scenarios - Write policy guidance on facial recognition, voice cloning, and geolocation inference, specifying which uses require consent and which are prohibited outright - Map the surveillance lifecycle, from target selection and data collection through analysis and covert deployment, and define the policy line at each stage so that interventions can occur early in the chain - Design and oversee evaluations that measure the model's capability to support social media monitoring, people-finding, predictive profiling, and the identification or tracking of specific people, to build, develop and improve safeguards with cross-functional partners to prevent malicious behaviors - Write and refine external-facing Usage Policy language and develop training guidelines, assessment rubrics, and evaluation protocols for enforcement teams, with emphasis on indicators of covert monitoring and population-level targeting - Validate enforcement decisions and automated assessments, provide policy guidance on complex edge cases such as investigative research into surveillance tools, coordinate with civil society, privacy experts, threat intelligence researchers, and academics, and serve as the escalation point for complex integrity and surveillance cases Minimum qualifications - Working knowledge of how deceptive campaigns and covert monitoring operate in practice, including account networks, bot operations, data aggregation pipelines, and attribution methods - Familiarity with surveillance technologies and their misuse, including social media monitoring tools, people-search services, location tracking, spyware, facial recognition, and open-source intelligence techniques used against individuals - General knowledge of the global regulatory landscape around data protection, privacy, platform regulation, and digital services accountability - Strong policy writing skills, with the ability to translate complex threat frameworks into clear, enforceable guidelines - Experience designing policies and workflows that enable both clear human enforcement decision-making and technical implementation in ML classifiers and detection pipelines - Strong collaboration skills and extensive experience partnering with Engineering, Data Science, Legal, Threat Intelligence, and Policy teams on cross-functional initiatives - Excellent written and verbal communication skills, with the ability to explain deceptive tactics, surveillance methods, and policy rationales to diverse audiences, including non-specialists and policymakers Preferred qualifications - 5+ years of experience in policy development, trust and safety, threat intelligence, or platform integrity, with hands-on work on inauthentic behavior, surveillance-related abuse, or data misuse - Experience in privacy policy, privacy engineering, or data protection work, including familiarity with privacy impact assessments and data minimization principles - Experience in intelligence roles, state-aligned monitoring operations, or covert data collection campaigns - Experience investigating inauthentic networks, covert monitoring, or surveillance abuses at a platform, research organization, or government body - Background in digital forensics, open-source intelligence, or threat attribution - Knowledge of persuasion theory, cognitive biases, and deceptive communication techniques, including social engineering and pretexting methods - Familiarity with human rights and privacy frameworks as they apply to surveillance, including protections for journalists, activists, and marginalized communities - Experience with trust and safety operations involving content moderation evasion, bot detection, or platform scraping enforcement - Experience working with EU institutions, regulatory bodies, or policy organizations on AI governance or digital platform regulation - Experience conducting adversarial testing, red teaming, or vulnerability assessments for AI systems or platforms, particularly for misuse involving monitoring or profiling - Familiarity with generative AI capabilities and an understanding of how LLMs can be used for synthetic personas, social engineering, predictive profiling, or surveillance at scale The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $245,000 - $285,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. As a manager of Applied AI Engineers for Anthropic's Megas segment, you will lead a team of deeply technical engineers embedded with our largest and most strategic accounts. These companies are partner-customers: they are among our biggest revenue drivers and also some of our most important go-to-market distribution channels. Each one consumes Claude to transform its own business and distributes Claude through its platforms and marketplaces. Your team works hands-on with their product and engineering organizations as they build on Claude: co-designing complex technical solutions, advising on architecture, developing evaluation frameworks, and guiding them through the most advanced implementation patterns for LLMs. You will hire, coach, and grow this team while staying close enough to the technology to set a high bar for engineering judgment. Your engineers work in account-aligned pods alongside Applied AI Architects, and you'll partner closely with pod leads, Mega Sales, Partnerships, Product, and Research. You'll guide your team from technical discovery through production deployment, turn wins at one Mega into reference architectures and patterns that compound across the others, and channel Mega-driven requirements back into Anthropic's product and research roadmap, all while maintaining our high standards for safety and reliability. This is a fast-moving space at the frontier of what's possible with LLMs, and you'll help define how we scale technical impact across our most important relationships. Responsibilities - Build, coach, and grow a team of Applied AI Engineers serving Mega accounts: hire strong technical builders, develop them through structured feedback and clear competency expectations, and create scalable onboarding for a customer-facing technical role. - Staff engineers into account-aligned pods alongside Applied AI Architects, balancing deep account continuity with flexibility to move expertise where the segment needs it most. - Set performance goals aligned with each Mega's technical account plan and the segment's consumption objectives, and establish the metrics, reporting cadence, and dashboards that keep pod leads and cross-functional stakeholders informed on team health and impact. - Serve as a senior technical advisor to Mega product and engineering leaders as they deploy production Claude workloads: guiding architecture design, evaluation strategy, and advanced prompting, agentic, and implementation patterns from discovery through deployment. - Lead hands-on co-build initiatives with Mega engineering teams, from prototypes and pilots to production deployments, in support of each account's joint roadmap with Anthropic. - Help navigate the partner-customer duality: support both direct consumption and the distribution of Claude through Mega platforms and marketplaces, and exercise sound judgment about what we build together and share. - Act as a technical escalation point for your team's accounts, and partner with pod leads and Mega Sales to sequence technical work for maximum customer value. - Build shared assets across pods, including reference architectures, agentic patterns, and eval frameworks, so that what one pod learns benefits every Mega account. - Collaborate with Product and Research to surface Mega-driven requirements with the right weight and context, advocating for high-impact product changes without becoming a feature-request pass-through. - Champion scalable public and internal assets documenting the latest LLM prompting, evaluation, agentic, and architecture techniques; contribute thought leadership through talks, blog posts, and white papers. - Maintain strong, current knowledge of LLM capabilities, implementation patterns, and the AI product development stack, and translate it into practical guidance for your team and customers. - Travel to customer sites for workshops, executive technical sessions, implementation support, and relationship building, and represent Anthropic at conferences and speaking engagements. You may be a good fit if you have - 6+ years of experience in technical roles such as Forward Deployed Engineer, Software Engineer, Solutions/Sales Engineer, or Technical Product Manager. - 4+ years of experience operating in a formal leadership capacity, ideally with some tenure as a manager of managers/multiple teams. Former technical founders are also encouraged to apply. - Demonstrated success hiring, coaching, and scaling customer-facing technical teams, ideally in a fast-moving or hypergrowth environment. - Experience supporting large, named strategic accounts at a platform, infrastructure, or model company, ideally where the account was both a customer and a partner. - Production experience with LLMs, including advanced prompt engineering, agent development and frameworks, evaluation frameworks, transcript analysis, MCP, and deployment at scale, with the technical depth to set engineering standards and review your team's work credibly. - Strong programming skills with proficiency in Python or TypeScript and experience building production applications. - A track record engaging senior technical stakeholders (CTOs, CPOs, and engineering leaders) and influencing technical architecture and partner product roadmaps. - Experience working in or running mixed pre-sales and hands-on engineering teams (for example, SA + FDE or SE + delivery). - The ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems. - A high-cooperation mindset for cross-organizational collaboration across Sales, Partnerships, Product, and Research, balancing competing priorities with integrity. - Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach. - Passion for advancing safe, beneficial AI systems through creative technical applications. Strong candidates may also have - Background at a hyperscaler, foundation model lab, or large ISV in a strategic-accounts or alliances technical role. - Experience with marketplace, embed/OEM, or co-sell motions. - Prior forward-deployed engineering leadership. - Experience leading technical teams through periods of rapid scale, balancing immediate execution with durable, long-term architectural and platform decisions. - Experience coaching engineers from purely technical roles into customer-facing, advisory work. - Executive briefing and public speaking presence. Deadline to apply None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 - $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. The Role: GPUs are the most expensive and supply-constrained input in AI. Our ability to effectively deploy them towards our customer demand is one of the critical inputs to our growth. We're hiring our first Data Scientist to build and own the quantitative models that drive pricing, packaging, and capacity allocation in order to optimize capacity and balance supply with demand. The ideal candidate brings expertise at the intersection of operations research and economics with the ability to both model our market, build dynamic pricing models, and design experiments and causal studies. This is a hands-on role: you'll write production-quality code, ship models that drive real decisions, and bring an true ownership mentality to help set priorities in addition to executing on them. What You'll Work On: Supply/Demand Modeling - Build fill-rate models for serverless inference, balancing utilization against performance and latency targets. - Model how traffic is shared and multiplexed across models and customers to set safe capacity buffers. Pricing Optimization - Design pricing for low-utilization capacity, including spot and preemptible offerings, off-peak and overnight windows, and sub-scale capacity pools. - Develop pricing policies to optimize our capacity utilization and price-yield. - Design execute experiments and causal studies to estimate elasticity across customer segments, models, and products. GPU Mix Optimization - Optimize the model-hardware matching across GPU generations, vendors, clouds, and regions, accounting for workload fit, substitution, and lead times. - Optimize our capacity across commitment types and terms, quantifying the tradeoff between cost, flexibility, and utilization risk to guide how we source capacity. What we’re looking for: Minimum Qualifications - Master’s degree in Operations Research, Economics, Industrial Engineering, Statistics, or a related quantitative field with 7+ years of hands-on experience in pricing, revenue management, or optimization. PhD preferred. - Strong grounding in at least two of: stochastic optimization, revenue management and pricing, causal inference and experimental design, or combinatorial optimization. - A track record of delivering production quality models that drive direct business impact. - Strong coding skills and experience with optimization tooling & methodologies. - Ability to communicate tradeoffs and uncertainty clearly to engineers and executives. Preferred Qualifications - Experience on capacity planning, forecasting, or pricing science teams at a cloud computing provider or marketplace business. - Familiarity with GPU infrastructure and LLM inference economics (throughput, batching, utilization, cost per token). - Experience as the first quantitative hire in a new function, building models and data pipelines from scratch. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. The Role Partnerships are a core growth motion at Fireworks, from cloud co-sell and marketplace motions to system integrators and technology partners. The Head of GTM Strategy & Ops - Global Partnerships is the business partner and strategic thought partner to the VP of Partnerships and the partnerships leadership team. You turn partner strategy into measurable pipeline stages, a reliable weekly operating cadence, and planning and capacity decisions. You will sit inside the Sales Strategy & Analytics team and work every day with partnerships leadership, partner managers, direct sellers and Finance. You will make partner-sourced and partner-influenced pipeline visible and trustworthy, run the partner forecast and pipeline reviews, and set the rules that keep partners and direct sellers working together. This is a builder role in a fast-moving startup. Some tooling and reporting exist, much of the operating system around them does not, and priorities change quickly. The right candidate is comfortable defining the process, doing the analysis themselves, and working with partnerships, sales, finance and engineering teams to get it adopted. Fireworks sells on consumption and hybrid commit + usage models, so experience with usage-based revenue is a strong plus. Responsibilities Business Partnership & Strategy - Act as strategic thought partner to the VP of Partnerships on where to focus, where to invest and what to stop across partner motions. - Help segment and tier partners, and translate partner strategy into joint plans, priorities and measurable goals. - Run the weekly, monthly and quarterly business reviews for Partnerships, with clear decisions, owners and deadlines. - Prepare executive and board-ready updates on the partner flywheel with the VP of Partnerships. Partner Pipeline, Forecast & Analytics - Define stage progression, sourced versus influenced attribution and credit rules for partner pipeline with Sales, RevOps and Finance. - Run the partner pipeline and forecast review: inspect deals, pressure-test commits and surface risk early. - Own the partner funnel analytics (stage conversion, win rate, sourced versus influenced split), ready for QBRs. - Define requirements for partner dashboards, forecasting views and alerts with GTM Analytics and GTM Engineering, and push for automation of weekly reporting. Planning, Targets & Capacity - Drive partner annual and in-year planning with Partnerships leadership, Sales and Finance. - Set partner pipeline and revenue targets in alignment with the VP of Partnerships and sales leadership. - Model partner team capacity and give hiring recommendations that tie headcount to pipeline and revenue goals. - Work with Incentive Strategy on how partner contribution is credited and rewarded. Partner Operations & Processes - Define rules of engagement between partners and direct sellers, including account ownership, deal credit and conflict resolution. - Build and maintain co-sell and referral processes, deal registration and CRM hygiene for partner data. - Partner with Enablement to onboard partner managers and sellers on partner motions and tools. - Track return on partner events and programs. Cross-Functional & AI-Native Ops - Partner with Finance, Legal, Marketing, Product and Field Engineering so partner priorities are heard and consistently planned for. - Use AI and agentic tooling in everyday work, and help partnerships and sales teams do the same. Qualifications - 7+ years in partnerships operations, strategy and operations, alliances, sales operations or consulting, including experience as a business partner to a partnerships or sales leader - Experience building partner pipeline reporting, attribution and forecasting, and a record of making the numbers trusted - Experience with co-sell, channel, alliance or marketplace motions - Experience running business reviews or forecast calls that produce decisions - Strong analytical skills, with comfort in SQL or BI tools - Credibility with senior leaders and the ability to influence without formal authority - Comfortable with ambiguity and building structure in a fast-moving startup - Experience building teams and processes as a business grows and scales - BA/BS degree in a quantitative field preferred Preferred - Experience at an AI/ML infrastructure, developer tools, or API-first company - Experience with cloud marketplaces and hyperscaler co-sell programs - Experience with usage-based or hybrid commit + usage revenue models - Familiarity with Salesforce partner data and partner relationship management tools - Hands-on experience building workflows with AI or agentic tools Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. À propos du poste En tant que leader de deuxième niveau pour l’équipe Applied AI Industries en Europe du Sud et au Moyen-Orient chez Anthropic, vous piloterez l’adoption d’une IA de frontier en partenariat avec le reste de l’organisation de mise sur le marché. Nos clients Industries en France, Ibérie et Italie incluent de nombreuses plus grandes entreprises de la région dans les services financiers, santé et sciences de la vie, fabrication, télécommunications, commerce de détail, énergie et autres secteurs. Vous mettrez à profit votre expérience de construction et de direction d’équipes de vente technique pour piloter une transformation IA positive qui répond aux besoins métier de nos clients, satisfait à leurs exigences techniques et réglementaires, et offre un haut degré de fiabilité et de sécurité. Vous serez responsable de la direction et de la croissance de l’équipe d’architectes de solutions qui partenaire avec les directrices et directeurs de compte pour aider les entreprises à adopter et déployer les produits d’Anthropic, notamment Claude Cowork, Claude Code et la Plateforme de Développement Claude (notre API). Cela inclura l’utilisation de vos compétences techniques et votre expérience de vente consultative pour recruter d’excellentes personnes en première ligne de management et contributeurs individuels, établir des processus pour évoluer votre équipe, et représenter Anthropic directement dans les engagements clients stratégiques. Votre équipe couvre plusieurs pays et secteurs à la fois, vous serez donc responsable de la réflexion stratégique sur les comptes d’industrie complexes et de l’identification et du déploiement de solutions qui résonnent dans chaque marché, avec sa propre langue, sa culture métier et son contexte réglementaire. Responsabilités - Recruter, manager et guider une équipe de managers de première ligne qui construiront à leur tour des équipes d’Applied AI Architects (H/F) de pré-vente en France, Ibérie et Italie - Définir les objectifs de votre équipe en collaboration avec le leadership commercial et établir les attentes de performance de base sur votre équipe - Agir en tant que sponsor technique et exécutif pour les clients stratégiques de haute valeur dans la région et les conseiller sur leurs stratégies globales d’adoption de l’IA ou la délimitation des cas d’usage et l’exécution de pilotes - Collaborer étroitement avec le leadership commercial d’Europe du Sud (couvrant également le Moyen-Orient et l’Afrique) pour construire des stratégies pour les comptes d’industrie complexes et identifier de nouvelles façons de piloter l’adoption des produits Anthropic dans des secteurs verticaux spécifiques ou des cas d’usage horizontaux - Aider les clients à naviguer dans les exigences réglementaires locales et européennes (par exemple, la Loi sur l’IA de l’UE, le RGPD, DORA et les attentes de résidence des données) et adapter la façon dont votre équipe s’engage à la culture métier de chaque marché - Travailler avec des équipes interfonctionnelles comme le produit et l’ingénierie pour assurer qu’Anthropic priorise les commentaires des clients ou résout les obstacles à l’adoption dans la région - Voyager régulièrement en Europe du Sud pour les clients ou conférences pour des sessions de haut niveau, des ateliers techniques et la construction de relations - Établir une vision commune pour créer des solutions qui permettent une IA bénéfique et sûre dans les produits technologiques - Contribuer à la pensée stratégique par des présentations en conférences, des webinaires et la création de contenu technique - Rester au courant des tendances émergentes en IA et du paysage concurrentiel Ce profil est un bon ajustement si vous : - Avez 7+ ans d’expérience en gestion de pré-vente technique, incluant un leadership de deuxième niveau ou supérieur (direction de managers) - Avez vendu des produits techniques complexes aux grandes entreprises en France, Ibérie, Italie, Moyen-Orient et Afrique - Avez travaillé dans plusieurs secteurs, tels que services financiers, santé et sciences de la vie, fabrication, télécommunications, commerce de détail et énergie - Comprenez les différences culturelles entre les marchés d’Europe du Sud et le contexte réglementaire dans lequel opèrent vos clients, et adaptez votre approche à chacun - Pensez de façon hautement stratégique aux comptes d’industrie complexes et transformez cette réflexion en plans que votre équipe et vos homologues commerciaux peuvent exécuter - Avez une profonde maîtrise technique des cas d’usage IA en entreprise, des intégrations d’API et des déploiements LLM - Prospérez dans la construction et l’évolution rapide d’équipes et de processus dans des environnements ambigus et mouvants - Ayez d’excellentes compétences en communication, collaboration et coaching - Ayez une présence exécutive forte et la capacité à cultiver des relations profondes avec les leaders métier et technique des plus grandes entreprises de la région - Ayez au moins une familiarité de haut niveau avec l’architecture et le fonctionnement des LLM - Ayez une passion pour rendre les technologies puissantes sûres et bénéfiques pour la société - Restiez à jour et informée en vous intéressant activement à la recherche émergente et aux tendances du secteur en IA Les candidates et candidats solides pourraient avoir : - Leadership de pré-vente d’entreprise à grande échelle : 5+ ans de direction d’équipes d’architectes de solutions à travers une hypercroissance (idéalement des dizaines de personnes dans plusieurs pays), avec expérience directe de direction de managers et développement de talents dans des environnements de vente de logiciels d’entreprise complexes - Gamme multilingue et multiculturelle : En plus de l’anglais, maîtrise d’une ou plusieurs langues parmi le français, l’italien, l’espagnol ou le portugais, et expérience de direction d’équipes distribuées dans plusieurs pays - Expérience avec les modèles commerciaux basés sur la consommation : Les candidats idéaux ont construit des cadres GTM ancrés sur la consommation, pas seulement sur les licences basées sur SaaS - Profondeur technique en IA + Engagement exécutif : Expérience pratique avec les plateformes d’IA et les modèles d’intégration d’entreprise, combinée à un historique avéré d’engagement des parties prenantes au niveau C dans des évaluations techniques de 10 M€+ et des cycles de vente d’entreprise - Expérience GTM multi-secteurs dans les secteurs réglementés : Succès démontré dans l’adaptation des approches techniques à différents secteurs verticaux, en particulier les secteurs réglementés tels que la banque, les assurances et la santé, y compris le travail avec les parties prenantes en matière de risque, de conformité et de comité d’entreprise About the Role: As the 2nd-line leader for the Applied AI Industries team in Southern Europe and the Middle-East at Anthropic, you will drive the adoption of frontier AI in partnership with the rest of the go to market organization. Our Industries customers in France, Iberia and Italy include many of the region's largest enterprises across financial services, healthcare and life sciences, manufacturing, telecom, retail, energy, and other sectors. You'll leverage your experience building and leading technical sales teams to drive positive AI transformation that addresses our customers' business needs, meets their technical and regulatory requirements, and provides a high degree of reliability and safety. You will be responsible for leading and growing the solutions architect team that partners with account executives to help companies adopt and deploy Anthropic's products, including Claude Cowork, Claude Code, and the Claude Development Platform (our API). This will include leveraging your technical skills and consultative sales experience to hire great 1st line managers and individual contributors, establish processes to scale your team, and represent Anthropic directly at strategic customer engagements. Your team covers several countries and industries at once, so you will be responsible for thinking strategically about complex industry accounts and for identifying and rolling out solutions that resonate in each market, with its own language, business culture, and regulatory context. Responsibilities: - Hire, manage, and guide a team of 1st line managers who will in turn build teams of pre-sales Applied AI Architects across France, Iberia and Italy. - Set goals for your team in collaboration with sales leadership and establish baseline expectations for performance across your team. - Act as a technical and executive sponsor for high-value strategic customers in the region and advise them on their overall AI adoption strategies or use case scoping and pilot execution. - Partner closely with Southern Europe sales leadership (also covering the Middle-East and Africa) to build strategies for complex industry accounts and identify new ways to drive adoption of Anthropic products within specific verticals or horizontal use cases. - Help customers navigate local and European regulatory requirements (for example the EU AI Act, GDPR, DORA, and data residency expectations) and adapt how your team engages to the business culture of each market. - Work with cross-functional teams like product and engineering to ensure Anthropic prioritizes customer feedback or resolves blockers to adoption in the region. - Travel regularly across Southern Europe to customers or conferences for executive-level sessions, technical workshops, and relationship building. - Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products. - Contribute to thought leadership through conference presentations, webinars, and technical content creation. - Stay current with emerging AI trends and the competitive landscape. You may be a good fit if you: - 7+ years of technical pre-sales management experience, including 2nd-line leadership or above (leading managers). - Have sold complex technical products to large enterprises in France, Iberia, Italy, the Middle-East and Africa. - Have worked across multiple industries, such as financial services, healthcare and life sciences, manufacturing, telecom, retail, and energy. - Understand the cultural differences between Southern European markets and the regulatory context your customers operate in, and adapt your approach to each. - Think highly strategically about complex industry accounts, and turn that thinking into plans your team and sales counterparts can execute. - Have deep technical proficiency with enterprise AI use cases, API integrations, and LLM deployments. - Thrive in building and rapidly scaling teams and processes within ambiguous and fast-moving environments. - Have excellent communication, collaboration, and coaching abilities. - Strong executive presence and ability to foster deep relationships with business and technical leaders at the region's largest companies. - Have at least a high level familiarity with the architecture and operation of LLMs. - Have a passion for making powerful technology safe and societally beneficial. - Stay up-to-date and informed by taking an active interest in emerging research and industry trends within AI. Strong candidates may have: - Enterprise pre-sales leadership at scale: 5+ years leading solution architect teams through hypergrowth (ideally dozens of people across several countries), with direct experience leading managers and developing talent in complex enterprise software sales environments. - Multilingual and multicultural range: In addition to English, fluency in one or more of French, Italian, Spanish or Portuguese, and experience leading teams distributed across several countries. - Experience with consumption business models: Ideal candidates have built GTM frameworks anchored on consumption, not just SaaS-based licenses. - AI Technical Depth + Executive Engagement: Hands-on experience with AI platforms and enterprise integration patterns, combined with proven track record engaging C-level stakeholders in €10M+ technical evaluations and enterprise sales cycles. - Multi-industry GTM experience in regulated sectors: Demonstrated success adapting technical approaches to different verticals, in particular regulated ones such as banking, insurance, and healthcare, including working with risk, compliance, and works council stakeholders. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: €265.000 - €310.000 EUR Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. About the Team The AI Performance team brings up and optimizes foundation models such as DeepSeek, Llama, Qwen, and GPT OSS on SambaNova's dataflow platform. We profile and tune models across the compiler, runtime, and hardware layers to improve inference throughput and latency. About the Role As a new grad AI Performance Engineer, you'll bring up new open source models on the SambaNova stack and work to make them run faster. You'll profile model execution, find bottlenecks, and apply optimizations such as quantization, kernel fusion, and improved scheduling with the compiler, runtime, and hardware teams. Responsibilities - Bring up new foundation models on the SambaNova platform using our software stack - Profile model performance across the compiler, runtime, and hardware layers - Identify bottlenecks and propose dataflow or scheduling optimizations for single-node and distributed systems - Apply techniques from recent research in quantization, scheduling, and memory optimization - Benchmark throughput and latency and track performance changes across releases - Work with the machine learning, compiler, runtime, and hardware teams to ship performance improvements into SambaNova products Required Qualifications - B.S. in Computer Science, Electrical Engineering, or related field - Strong programming skills in Python or C++ - Understanding of algorithms, data structures, and numerical computing - Experience with PyTorch, TensorFlow, or JAX - Experience with inference frameworks such as vLLM, TensorRT, or SGLang - GPU programming experience with CUDA or Triton Preferred Qualifications - M.S. or Ph.D. in Computer Science, Electrical Engineering, or related field - Experience with LLM training or inference - Familiarity with quantization, graph optimization, kernel fusion, or model partitioning - Knowledge of memory hierarchy, caching, and scheduling for large model execution - Internship or research experience in ML systems or performance optimization - Publications or open source contributions in ML systems Base Salary Range: Base Pay Range $131,200 - $196,800 USD Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified. EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic Australia, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises across Australia and the Asia-Pacific region understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with both the Claude API and Claude for Work - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel occasionally within Australia and the APAC region to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns - Collaborate across time zones with global teams while serving as the technical expert for the Australia market You may be a good fit if you have: - 10+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Experience working with enterprise customers in Australia or the APAC region, navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Comfortable with Python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems - Ability to work effectively across cultures and time zones as part of a global team Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the Together GPU Clusters flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Staff Software Engineer focusing on AI Compute in the Together Cloud org, you will set technical direction for and build major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. This is an architect-and-build role. Fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes — you'll set the architecture for these across our global and in-DC services, and be a key owner of the hardest parts, in the code as well as the design. Your designs will span the IaaS layer of a greenfield Vera Rubin data center up to the global management plane that schedules capacity across all of them. At this level the job is as much leverage as code: the standards you set and the engineers you grow decide how fast the rest of Together Cloud ships. Responsibilities - Own the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that keeps GPU compute and DC networking high-performance, portable, and strongly isolated across heterogeneous hardware. - Own the in-DC IaaS layer: architect and roadmap the services, Kubernetes operators, and libraries that provision and manage compute, storage, and networks in our data centers — VMs, parallel filesystems, VPCs, and InfiniBand partitions; lead its build-out for a new Vera Rubin data center with thousands of GPUs, from hardware bring-up to customer-facing API. - Design the GPU scheduling and global management plane: the distributed control plane behind on-demand and reserved clusters across dozens of data centers, including the systems that scale per-cluster limits and automate the onboarding of new capacity. - Architect monitoring and automated remediation for fault tolerance: the strategy for automated detection, isolation, and recovery of failed nodes that keeps distributed pretraining and large-scale inference running through hardware failures. - Set technical direction across teams: lead design reviews, resolve cross-cutting architectural disagreements, unblock cross-team dependencies and integration risks, and define the standards other engineers build against — measured in cluster reliability, time-to-first-GPU on new capacity, and quality at scale. - Grow the team: mentor senior and junior engineers, deepen the team's expertise in virtualization, DC networking, and GPU infrastructure, and help raise the hiring bar for Together Cloud. - Set the engineering bar: create the testing frameworks, tools, and developer documentation that make our systems robust and usable by other teams, and shape the core, open-source Together AI platform. To be successful you'll need to be deeply technical and an excellent communicator — expert software development fundamentals, deep systems knowledge and troubleshooting instincts, and the leadership and diplomacy skills to align teams that don't report to you. Much of this work starts ambiguous, and we expect you to define the scope yourself and drive it to production. Requirements - 7+ years of professional software development experience, with expert-level proficiency in at least one backend language (Golang desired), writing high-performance, well-tested, production-quality code. - Track record of owning the architecture of large distributed systems from blank page to production at scale, including the judgment calls that could not be reversed cheaply. - Deep experience building and operating globally distributed, high-performance microservice architectures across one or more cloud providers (AWS, Azure, GCP). - Expert systems knowledge across compute, networking, and storage — including concurrency, memory management, performant I/O, and scale at a global level. - Demonstrated technical leadership beyond your own commits: mentoring senior engineers, leading design reviews, and driving alignment across teams that do not report to you. - Excellent communication and diplomacy skills — able to write design docs that settle arguments, and to work effectively with technical and non-technical stakeholders. - Experience building and operating reliable, customer-facing production systems at scale, and owning the infrastructure automation (Terraform, Ansible), observability (Prometheus, Grafana), and CI/CD (GitHub Actions, ArgoCD) that keep them healthy. Preferred Qualifications (not must haves) - Deep Kubernetes internals experience, such as implementing non-trivial Kubernetes operators, device/storage/network plugins, custom schedulers, or patches to Kubernetes itself - Deep experience with VMs/hypervisors, such as QEMU/KVM, cloud-hypervisor, VFIO, virtio, PCIE passthrough, Kubevirt, SR-IOV - Deep experience with DC networking tech + solutions, such as VLAN, VXLAN, VPN, VPC, OVS/OVN - Experience with Cluster API or similar - Experience working on high-performance compute, networking, and/or storage - Experience virtualizing GPUs and/or InfiniBand - Experience building IaaS or PaaS systems at scale - Experience with DPUs/SmartNICs - GPU programming, NCCL, CUDA knowledge About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Application Policy Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy

SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. We are looking for a technical product manager to own SambaNova's model and capability roadmap end to end. You will be the product owner and the subject-matter expert on models: you understand why a model matters (architecture, benchmarks, adoption, customer pull) and what it takes to ship it well (function calling, structured output, reasoning, long context, caching, speculative decoding and more). Most importantly, you turn that understanding into decisions, commitments and launches. This is a product role for someone deeply technical, not an engineering role with product tasks attached, but you will stay hands-on: testing new models yourself, finding where they shine and where they break, and building quick mock-ups that show the competitive edge fast inference unlocks. Responsibilities Own and drive the roadmap - Model Stack Rank: Own the unified, weighted stack rank of candidate models across customer demand, capability, market adoption, recency, strategic value and engineering effort. Tune the rubric, make and document overrides, and run the regular prioritization review - Per-Chip Roadmap: Own the plan of models × hardware generation × configuration × performance targets, and keep it grounded in measured platform data rather than estimates - Commitments and Launches: Turn priorities into dated commitments with engineering, track them to delivery and run model launches with Marketing, Docs and GTM - Roadmap Communication: Keep the model roadmap and dashboard current as the source of truth for execs, account teams and customers, and present it with confidence both internally and externally Define the capability bar - Feature-Completeness Framework: Own the definition of a “fully featured” model across speed, efficiency, model infrastructure, cloud and API features, for example tool calling, JSON schema and constrained decoding, reasoning controls, full context length, prompt caching, speculative decoding, streaming, logprobs and API compatibility (OpenAI Chat, Responses, Anthropic) - Gap Management: Find capability and conformance gaps from testing and telemetry, set their priority and drive them to closure with engineering - Quality Bar: Work with QA and Solutions to set acceptance criteria and the evals a model must pass before it launches Get hands-on with models - Model Testing and Evaluation: Get your hands on new models as soon as they land: run them through real prompts, agentic tasks and our feature checks to learn what works well, what does not, and where the gaps are - Finding the Edge: Spot the models, capabilities and use cases where SambaNova's speed and efficiency create a real competitive advantage, and back that view with evidence - Prototypes and Mock-ups: Build quick demos, prototypes and product mock-ups (e.g. a small app, notebook or UI) that make a model's value concrete for leadership, GTM and customers, and hand the strongest ideas to Solutions Engineering to productionize - Hands-on Findings to Roadmap: Feed what you learn into the stack rank, the feature bar and launch messaging, so roadmap decisions draw on first-hand experience as well as the data Be the model SME - Market and Model Intelligence: Track the open-weight model landscape (new releases, architectures such as MoE, MLA and GQA, benchmark and usage signals from sources like Artificial Analysis, OpenRouter and Hugging Face) and form a clear view on what matters and why - Customer Voice: Take in requests from customers, the field and the Model Feedback process, triage them, close the loop with requesters, and make sure demand is represented accurately in the rank - Competitive Positioning: Understand how our models, speed and features compare with GPU clouds and other inference providers, and turn that into roadmap and messaging - Process and Tooling: Keep improving the roadmap process and its data pipeline (Jira, internal platform APIs, public signals) so it stays trustworthy, auditable and as automated as possible Requirements Required Qualifications - Bachelor's degree or higher in Computer Science, Engineering, Machine Learning or a related technical field - 7+ years of combined experience in product management and technical roles (ML engineering, solutions engineering, research), including 3+ years as a PM on AI/ML, developer or infrastructure products - Strong working knowledge of LLMs: transformer and MoE architectures, inference trade-offs (latency, throughput, context, quantization), and features such as function calling, structured output and reasoning - A track record of owning a roadmap and shipping: setting priorities under constraints, saying no with data, and driving cross-functional teams to launch - Comfort with data: building and maintaining prioritization models, dashboards and scorecards, and hands-on enough to query an API or change a Python script - Hands-on with models: comfortable calling model APIs, running evals and quick experiments, and building simple prototypes or mock-ups (Python, notebooks or lightweight UI tools, including AI coding assistants) - Excellent written and verbal communication, with the ability to present a roadmap and defend trade-offs to executives, engineers and customers Preferred Qualifications - Product experience at an inference provider, model lab, AI cloud or AI hardware company - Hands-on familiarity with inference stacks (vLLM, SGLang, TensorRT-LLM) and OpenAI/Anthropic-compatible APIs - Experience designing evals and benchmark methodology for model quality and feature conformance - A background as an ML or solutions engineer before moving into product - Experience with enterprise, sovereign AI or public-sector customers - An active presence in the open-source model community What Success Looks Like - First 90 days: Take ownership of the stack rank, per-chip roadmap and feature framework; run the prioritization review; get hands-on with the current top-ranked models; and publish a roadmap that GTM and engineering both sign up to - 6 months: Measurable cut in time-to-model for priority models, clear visibility into capability gaps for every launched model, and every customer request tracked and answered - 12 months: The model roadmap is seen as SambaNova's strategic advantage: predictable launches, fully featured models, and a roadmap the field sells against Base Salary Range: Base Pay Range $190,000 - $230,000 USD Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified. EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Applied AI team helps the world’s largest organizations put Claude to work. As a Cybersecurity Specialist on Applied AI, you’ll be part of an overlay team of domain experts who sit alongside our enterprise account teams and bring deep security expertise to the accounts where it matters most. You won’t own an account. You’ll be the security expert the account team pulls in to win and grow the most important security conversations: helping CISOs and security leaders see where Claude can take on real security work, then guiding them from early pilots to durable, production workloads. You’ll cover a portfolio of enterprise accounts across regulated industries like financial services, insurance, and healthcare, strategic accounts like semiconductors (IP protection, industrial control systems, export controls), and digital natives and public sector agencies, each with its own threat model. How this team works - You partner with account executives, account architects, and generalist Applied AI engineers, who own the customer relationship and the broader technical engagement. You bring the security depth they don’t have time to build. - You work across many accounts at once, so the playbooks, reference implementations, and evaluation approaches you build are reused across the field, not just for one customer. - You are the connection point between the field and Anthropic’s Product, Research, and Engineering teams, turning what you see in customer security programs into product feedback. - You work alongside ISVs, systems integrators, and managed security providers who already serve these customers, enabling them where they own the engagement rather than competing with them. Responsibilities - Join account teams to understand a customer’s security program, identify where Claude can do meaningful security work, and turn that into a technical plan and business case - Serve as the security-domain technical advisor on strategic enterprise accounts, from discovery through deployment - Move customers from one-time code scanning to sustained security workloads: application security in the SDLC, continuous automated penetration testing, alert triage and investigation, and threat intelligence that answers “does this new vulnerability affect us, and where” - Build and maintain reference implementations, harnesses, and evaluation approaches, and help customers adapt them to their own environments and controls - Run workshops and hands-on sessions where customer security teams use Claude on their own code and workflows - Equip partners to deliver Claude-powered security outcomes, with a clear line between what Anthropic delivers and what partners deliver - Speak credibly to every audience, from appsec engineers to CISOs and executives, including how to explain the value and risk of security work in business terms - Define and track adoption depth for each security workload across your accounts, and work with Product and Engineering on the telemetry to measure it - Write the playbooks and best practices the rest of the field can reuse, including how Claude complements the security tooling customers already own - Develop reference customers who can speak to the value they’re realizing - Stay current on frontier LLM capabilities and the new classes of vulnerabilities and attacks they surface - Travel occasionally to customer sites for workshops and technical deep dives You may be a good fit if you have - 5+ years in security roles, with hands-on depth in at least two of: application security and secure SDLC, offensive security and penetration testing, detection and response, or threat intelligence and vulnerability management - Experience in a technical customer-facing role (Solutions Architect, Sales Engineer, security consultant, TAM), or on a security team where you had to win investment from leadership - Experience with large enterprise customers and complex, multi-stakeholder buying cycles, including working alongside the vendors and partners already in the account - The ability to translate between security teams, engineering teams, and executives - Comfort with Python, CI/CD, and cloud environments, plus hands-on experience using LLMs for security work such as code review, vulnerability discovery, triage, or investigation - A love of teaching and a collaborative approach to working across teams and balancing competing priorities The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 - $400,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About the Role The Speculative Decoding team at Together AI builds the draft models and algorithms that let large language models generate faster without changing their outputs. Our speculators run in production on frontier open models such as DeepSeek, Kimi and GLM. Our work sits at the intersection of model training, inference algorithms and serving systems, and we co-design all three to lower the cost and latency of generation. As a research intern, you will dive into open questions in speculative decoding: new drafter architectures and verification schemes, knowledge distillation and training recipes that align draft and target models, and drafters that adapt as traffic shifts. You will train and fine-tune draft models at scale on dedicated GPU clusters, and test your ideas against realistic serving workloads, including long-context and agentic traffic. Projects aim to answer important research questions in speculative decoding, enabling faster generation on frontier models, drafters that keep pace with changing workloads, and robust, reproducible evaluation under real traffic. Past Research Speculative decoding research by Together researchers, interns and academic collaborators includes: - Speculative Speculative Decoding (ICLR 2026) - When RL Meets Adaptive Speculative Training: A Unified Training-Serving System (ICML 2026) - Beat the Long Tail: Distribution-Aware Speculative Decoding for RL Training (MLSys 2026) Responsibilities - Research and prototype new efficient speculative decoding algorithms and draft model architectures - Train, fine-tune and distill draft models, and design rigorous experiments to validate hypotheses. - Implement optimized version for serving engines to show efficacy in real world workloads - Communicate the plans, progress, and results of projects to the broader team - Share findings through technical write-ups and blog posts, and help bring successful ideas into production Requirements - Currently pursuing a Master's or Ph.D. degree in Computer Science, Electrical Engineering, or a related field - Strong knowledge of Machine Learning and Deep Learning fundamentals - Hands-on experience training or fine-tuning large models with distributed training frameworks (e.g., Megatron-LM, FSDP) - Familiarity with modern model architectures, such as Mixture-of-Experts and hybrid attention Preferred Qualifications - Prior research experience in speculative decoding, efficient inference, or efficient machine learning - Publications at leading conferences in machine learning or systems (e.g., NeurIPS, ICML, ICLR, MLSys) - Experience with knowledge distillation, post-training, or reinforcement learning - Familiarity with LLM serving engines (e.g., vLLM, SGLang, TensorRT-LLM) - Contributions to open-source machine learning projects About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Internship Program Details Our internship program runs 12 to 14 weeks, giving you the opportunity to work alongside industry-leading engineers and researchers across multiple teams. This cohort's internship dates span January 4th to April 9th. Compensation We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 - $70 an hour. Our hourly rates are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Application Policy Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. For more information about our privacy policy, please visit: https://www.together.ai/privacy

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers lead complex deployments of frontier models in production. You will embed with customers where model performance matters, delivery is urgent, and ambiguity is the default. You will use this to map their problems, structure delivery, and ship fast. As a Forward Deployed Engineer for AI Infra, you will work directly with customer engineers, researchers and product engineers on optimization problems across semiconductors and AI infrastructure. You will write and debug software, run experiments against real workloads and hardware, and improve the tools and product used across engagements. You will help define the problem and success criteria, build the software needed to test an approach, and stay with the work through validation and deployment. Work may include inference performance and chip-design optimization. Success means producing results that stand up to correctness and performance checks, and contributing improvements that other engagements can use. Success in this role means owning the delivery state across workstreams. You will hold the bar on quality and pace and help OpenAI learn through execution. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will: - Own technical delivery for agreed semiconductor and AI-infrastructure workstreams, from initial scoping and prototypes through validation, production deployment and adoption. - Work closely with customer engineers to understand their workflows and constraints, define workloads, baselines and success criteria, and help what you build become part of how they work. - Scope and sequence delivery , identify dependencies and blockers early, and make practical trade-offs between scope, speed and quality as the work develops. - Personally build and debug production-quality software , including harnesses, integrations and product features that apply frontier models to problems in chip design, verification, inference and performance engineering. - Design reproducible experiments, evaluations, graders and benchmarks to test approaches, validate correctness and performance, and establish whether improvements hold up in real engineering environments. - Investigate model behavior and failure modes alongside researchers , contributing evaluation or training data and targeted experiments where they can improve the underlying capability. - Contribute directly to core product development , working with product engineers to resolve tooling gaps, ship useful improvements and bring field learning into product decisions. - Lead technical discussions and maintain alignment across customer, Product and Research teams. Build the domain and product fluency to explain capabilities, limitations and results, and keep ownership, risks and next steps clear. - Turn successful approaches into reusable software, tools and playbooks , reducing the effort needed for future engagements and helping customer teams operate what has been built. You might thrive in this role if you: - Bring 5+ years of engineering or technical deployment experience that includes customer-facing work - Have scoped and delivered complex systems in fast-moving or ambiguous environments - Write and review production-grade software, and debug unfamiliar systems across code, integrations and runtime behavior. - Have built or deployed systems powered by LLMs or generative models and understand how model behaviour affects product experience - Simplify complexity and make fast, sound decisions under pressure - Communicate clearly with engineers, product teams, and customer stakeholders - Spot risks early and adjust without slowing down - Model calm and judgment when the stakes are high - Have a strong product sense and have contributed towards productizing efforts - Have hands-on experience with applied machine learning, model evaluation, data quality, experimentation, or model-behavior analysis - Can turn an ambiguous technical problem into a clear evaluation, a credible baseline, and a reproducible experiment - Are comfortable learning unfamiliar technical domains and working closely with researchers, product engineers and customer engineers. Experience in semiconductor development, data-center systems or inference engineering is helpful. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role: We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. Key Responsibilities: - Infrastructure & Platform Engineering : Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development : Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment : Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams What We're Looking For Required Experience 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect, Deployed Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences Key Attributes: - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience Compensation: $185,000-$260,000 base salary + equity Location: - Singapore - Remote with up to 25% travel Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Benefits Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role: We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. Key Responsibilities: - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. Requirements: - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. Nice to Have: - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers , or TRL. - Experience with trace mining to drive continuous improvement loops Compensation: $185,000-$260,000 base salary + equity Location: - Singapore - Remote with up to 25% travel Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Benefits Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

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Applied AI Architect (Brazil)

Negotiable

About the Team The AI Architect team partners with organizations to turn OpenAI's most capable models into meaningful, real-world impact. We work with customers across industries and digital-native businesses to identify where AI can create value, design secure and scalable solutions, and help those solutions move from early exploration into sustained production adoption. The team brings together technical strategy, customer partnership, and practical deployment expertise, working closely with Sales, Product, Engineering, Research, and specialist delivery teams. About the Role As an AI Architect, you will be the senior technical owner for a named portfolio of customers and the primary technical counterpart to their leadership teams. You will act as the “CTO of your book of business”, shaping each customer's AI strategy and guiding their journey from pre-sales discovery and solution evaluation through deployment, adoption, and measurable business impact. You will own the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex, and other agentic AI solutions. In partnership with the Account Director, you will translate business priorities into a focused use-case portfolio, an actionable adoption roadmap, and a clear path to durable customer value and growth. The Account Director owns commercial strategy; you own the technical strategy, customer journey, and path to production value. You will remain accountable for the technical outcome while bringing in the right specialists across deployment, implementation, enablement, security, product, and partners to provide deeper expertise and execute work where needed. This role calls for strong industry fluency, sound architectural judgment, and the ability to move confidently between executive strategy and hands-on technical conversations. In this role, you will: - Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing customers and pre-sales prospects. - Partner with Account Directors on account strategy while owning the technical account plan, technical milestones, adoption priorities, and expansion opportunities. - Lead discovery with executives and technical teams to identify, qualify, and prioritize use cases tied to meaningful business outcomes. - Develop clear Applied AI Architectures spanning models, applications, data, integration, security, privacy, governance, evaluation, and deployment. - Guide customers through technical evaluations, demonstrations, workshops, prototypes, and proofs of value, securing confidence in both the solution and its path to production. - Maintain a focused use-case portfolio with clear decision criteria, ownership, blockers, success measures, delivery needs, and adoption plans. - Develop trusted relationships and technical champions across CTOs, CIOs, CISOs, AI leaders, engineering teams, and other customer stakeholders. - Qualify and coordinate support from Deployment Engineering, implementation, training and enablement, product and domain specialists, partners, and other delivery teams. - Remain accountable for technical progress and customer outcomes while ensuring delivery teams own implementation execution once engaged. - Track adoption, usage, account health, production readiness, and measurable customer impact, intervening early when risks threaten value realization. - Apply industry or digital-native expertise to recognize repeatable patterns, sharpen customer priorities, and identify relevant expansion opportunities. - Share customer insights with Product, Engineering, and Research, translating field learnings into better products, architecture guidance, and reusable practices. You might thrive in this role if you: - Have significant experience in customer-facing technical roles such as solutions architecture, solutions engineering, technical account leadership, AI deployment, or technical customer success. - Have guided enterprise organizations from technical evaluation through production adoption and measurable business impact. - Build credibility with senior technical and business leaders while communicating equally well with hands-on engineers. - Bring strong software and cloud architecture foundations, including APIs, distributed systems, data integration, identity, security, and privacy. - Understand modern AI systems, frontier LLM models, agentic applications, model evaluation, retrieval, or enterprise AI workflows. - Can prototype, explain technical tradeoffs, and work confidently with APIs, SDKs, and languages such as Python or JavaScript. - Exercise sound judgment about when to go deep personally, when to involve specialists, and how to define clear handoffs and ownership. - Have experience developing technical account plans, prioritizing complex customer portfolios, and connecting adoption to measurable outcomes. - Bring meaningful expertise in a relevant industry or strong fluency with the needs of digital-native businesses. - Communicate clearly and can turn ambiguity into a practical technical narrative, executive decision, or action plan. - Work collaboratively across disciplines and care deeply about helping organizations deploy advanced AI responsibly. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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AI Deployment Manager - Builder

$240,000

About the Team The AI Deployment Manager (ADM) team enables organizations to turn OpenAI products into real, sustained impact through world-class enablement and training execution. Our mission is to help customers successfully adopt and operationalize AI across their organizations. We partner with enterprises to translate the potential of OpenAI’s technology into durable capability—through structured training, technical enablement, and scalable deployment programs. By helping customers move from experimentation to production, the ADM team accelerates time-to-value, deepens meaningful adoption, and helps make OpenAI indispensable to how organizations work. About the Role The AI Deployment Manager, Builder role is a specialist post-sales technical enablement role focused on delivering high-impact enablement and adoption services across OpenAI’s product suite. You will design and deliver technical learning experiences covering OpenAI APIs, Codex, agents, evaluations, and related platform capabilities. You will work with engineers, AI and platform teams, administrators, security stakeholders, product leaders, and executive sponsors. This role blends deep technical fluency, instructional design, and customer advisory. You will lead live trainings, workshops, and adoption interventions for audiences ranging from hands-on builders to executive leaders, helping customers understand not just what OpenAI’s products can do, but how to use them effectively in real-world contexts. Success in this role means accelerating customer confidence, increasing product adoption, helping customers progress toward production use, and turning lessons from individual engagements into resources and practices that benefit many customers. This role is based in San Francisco or New York. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own the technical enablement of OpenAI products, including OpenAI APIs, Codex, Agents, Evaluations and other platform capabilities, helping define effective enablement patterns that support adoption across customer segments - Lead customer training and enablement across the full customer lifecycle, from initial onboarding through expansion, optimization, and long-term adoption. - Design and deliver high-impact training engagements, including onboarding sessions, advanced capability trainings, executive briefings, hackathons, and hands-on workshops for audiences ranging from senior leaders to working teams. - Drive customer activation, sustained usage, and measurable business value through structured enablement and deployment programs designed for durable adoption at scale - Partner closely with Sales, Solutions Architecture, and Product teams to define an effective enablement plan tailored to each customer’s use case, goals, and technical needs. - Partner closely with Sales, Solution Architects, Delivery Leads to drive adoption across our core product suite. - Develop and refine reusable training assets, playbooks, and best practices based on patterns observed across customers and regions. - Gather customer feedback from training and enablement engagements, synthesize themes across accounts, and relay insights to internal stakeholders to inform product and program improvements. - Serve as a Subject Matter Expert (SME) for designated product areas, building deep expertise, supporting internal enablement, identifying emerging customer use cases for new product surfaces, and aggregating customer feedback to inform product development. You’ll thrive in this role if you: - Have 4+ years of experience in customer-facing or instructional roles, engaging C-level and senior technical audiences in complex enterprise environments. - Possess exceptional presentation and communication skills, particularly when conveying the value of technical concepts clearly to senior and executive-level audiences. - Strong technical depth across software engineering, the software development lifecycle, and APIs, with a practical understanding of how AI systems are built, evaluated, and operated in production, including RAG, evaluation strategies, agentic systems and key tradeoffs. - Proven experience leading structured technical trainings, such as API bootcamps, workshops, or enablement sessions, with the ability to design learning journeys, handle live questions, and reason through problems in real time. - Strong ability to connect technical features and capabilities to concrete business outcomes such as productivity, efficiency, cost reduction, risk mitigation, or revenue impact. - Have a humble attitude, an eagerness to help others, and a desire to pick up whatever knowledge you're missing to make both your team and our customers succeed. - Comfortable thinking on their feet in live customer settings, adapting quickly to new information, shifting priorities, and real-time questions while maintaining clarity, ownership, and momentum. - Are personally committed to fostering the safe and ethical evolution of AI. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

S

Quality Lead, Gen AI

Negotiable

The quality of data underpins Generative AI programs. At Scale, Quality Control is responsible for ensuring data we deliver to the world’s leading AI customers is state of the art. As a Quality Control Lead, you’ll own that call for some of our highest-impact Generative AI programs. You'll lead a large team of quality control specialists to measure and improve quality across these programs, from multilingual post-training data to agentic RL environments. You will work on frontier-level problems – the programs you work on train the models people are talking about. You will hold delivery teams accountable across our highest-impact projects – helping solve nuanced quality issues, as well as leading strategic initiatives to enable reliable, scalable operations across the organization. What you’ll do - Lead and grow a team of quality specialists - hire, coach and calibrate this team of specialists. - Turn unclear customer requirements into clear standards - work with delivery teams to interpret and improve customer requirements, and then turn that into measurable signals of data quality. - Run the quality system. Own the daily operation: plan and allocate workforce capacity, produce quality reporting, measure productivity and efficiency, and drive quality control policies. - Analyzing quality trends. Identify, root-cause, and elevate defect patterns that delivery teams can take action on. - Build the future of QC. Our team already leverages agentic capabilities, but you will help decide and lead what gets built next to continue to scale and optimize our quality operations. Ideally you’d have - A Bachelor’s degree in Computer Science, Engineering, Operations, or a related field. - 3+ years leading teams or scaling large operational/technical processes. - Strong analytical and problem-solving skills (particularly in SQL) with attention to detail. - Experience building systems, processes, and teams across multiple customer segments or product lines. - A hands-on background in product management, operations management, program management, or top-tier management consulting. - Proven experience taking initiative in cross-functional technical environments. Nice to haves: - Master’s degree in Computer Science, Engineering, Operations, or a related field. - Experience in AI/ML services, data annotation or model evaluation. - Experience in a fast-growing, less-structured startup environment. - Experience building teams from the ground up. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $134,400 - $168,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Agent Post-Training, Computer Use Research

$380,000 – $500,000

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might - Design and run experiments that improve agentic model behavior for complex computer use , including desktop and browser. - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. - Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements. - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. You might thrive in this role if you - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. - Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution. - Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with. - Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next. - Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group. - Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous. - Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Applied Scientist Lead (Robotics), EMEA

Negotiable

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role Mistral AI is seeking a Lead / Staff Applied Scientist to help lead our robotics research and industrial collaborations in the Applied Science team. You will set the technical direction for robotics, and design, train, and deploy SOTA robotics models (VLM, VLA models for navigation and manipulation) with our industrial partners. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions. We are made of researchers, engineers, product builders, ex-founders who love tackling the most complex real world problems in the industry. What you will do - Set the technical direction for robotics in Applied Science: which problems, models, data, and benchmarks we invest in. - Lead the technical execution of high-stakes robotics projects with customers and partners, from scoping to deployment. - Build and mentor a team of robotics Applied Scientists and Research Engineers. - Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. - Own the data strategy: generate and curate datasets (image-text, video-text, teleoperation, simulation), and build evaluators/benchmarks for perception, navigation and manipulation tasks. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams, and engage senior stakeholders. About you - Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences. - Experience leading a technical AI, science or engineering team. Balancing technical IC work with team leadership and stakeholder management. - Expert with PyTorch or JAX. - Deep experience with Vision Language Models (VLM), Vision-Language-Action (VLA) models, perception, navigation and manipulation, simulation tools (e.g. Isaac SIM), with a track record of shipping models on real robots. - Not afraid of contributing to a big codebase; finds their way around independently with little guidance. - Writes clean, readable, high-performance, fault-tolerant Python code. - Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. Nice to have - Ex-founder or builder - PhD / Master in a relevant field (Robotics, Machine Learning) — exceptional candidates from other backgrounds welcome. - Experience with sim-to-real transfer, world models, or large-scale robot data collection. - Experience working on large code bases or large machine learning models at scale. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

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Applied AI Architect, Public Sector (State & Local...

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping state and local government agencies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with Claude Code, the Claude API, and Claude for Enterprise - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel frequently to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: - Must have prior experience working with US federal, state, and/or local agencies - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Experience navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Familiar with Python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $275,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

A

Applied AI Architect, Public Sector (GovTech)

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping systems integrators, startups, and other GovTech companies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with Claude Code, the Claude API, and Claude for Enterprise - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel frequently to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: - US Secret Clearance preferred for working with defense tech customers - Prior work in government, government contracting, or government tech preferred - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Experience navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Familiar with Python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $275,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

A

Applied AI Architect, Public Sector (Federal Civil...

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping state and local government agencies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with Claude Code, the Claude API, and Claude for Enterprise - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel frequently to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: - Must have prior experience working with US federal, state, and/or local agencies - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Experience navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Familiar with Python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems About the role: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping federal civilian agencies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with Claude Code, the Claude API, and Claude for Enterprise - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel frequently to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: - Security clearance not required, but a plus - Must have prior experience working with US federal agencies - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Experience navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Familiar with Python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $275,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

A

Applied AI Architect ( Global Customers)

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic India, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises across India and the Asia-Pacific region understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with both the Claude API and Claude for Work - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel occasionally within India and the APAC region to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns - Collaborate across time zones with global teams while serving as the technical expert for the India market You may be a good fit if you have: - 10+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Experience working with enterprise customers in India or the APAC region, navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Comfortable with Python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems - Ability to work effectively across cultures and time zones as part of a global team Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

A

AI Outcomes Manager, Strategic Tech (Spanish-speak...

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Join Anthropic's Customer Success team in a high-visibility & high-impact role driving AI adoption across a small number of strategic accounts in our Enterprise Tech segment. As our dedicated Outcomes AI Manager for Strategic Tech Customers you’ll be their partner and trusted advisor helping them harness the full potential of all our Claude capabilities - API, Claude Code, Cowork, and other surface areas. You'll work with a book of global technology leaders to actively deploy AI and reshape the technology landscape. You’ll be working with key partners who are moving fast and pushing the boundaries of what's possible with LLM technology. Your role will entail developing genuine partnerships with the customer and key stakeholders, gaining a deep understanding of their multi-pronged business objectives, strategic direction, AI vision, and technical needs. You'll draw on both your business acumen and technical expertise to serve as a strategic advisor throughout their journey with us. In partnership with the broader account team, you will help customers identify the right Claude capabilities for their specific business objectives, working closely with them to provide best practices and guidance while supporting them as their usage grows and evolves. Your role focuses on helping customers scale their usage effectively, drive model and use case optimizations, implement change management strategies, and maximize the value of their investment through expanded use cases across their organization. The insights you gather from your customers will directly inform our research priorities, product development, and go-to-market strategies — making you a key voice in shaping how we build and deliver ongoing value as a business. Responsibilities: - Build trusting, strategic relationships with key customer decision makers in complex, matrixed organizations; understand their business and objectives and identify opportunities for optimization and expansion - Own customer operations across the lifecycle of each account, maintaining a structured operational assessment (customer readiness, operational health, strategic alignment, enablement strategy, adoption intelligence) that grounds comprehensive account and success plans and Executive Business Reviews - Become an expert in Anthropic's products across API, Claude Code and Cowork, understanding the technical nuances and best practices for each to guide customers to the right solutions - Leverage your deep knowledge of each customer, and the patterns you see across your other Tech accounts, to proactively drive consumption planning and the value story behind it, developing credible ROI hypotheses and quantifying outcomes that build the case for continued and expanded investment. - Monitor usage patterns and identify optimization opportunities across Claude surface areas (API, Claude Code, Cowork) to drive full value from contracted commitments - Serve as the customer’s thought partner, enhancing their knowledge of Claude products by socializing Anthropic’s product roadmap, driving awareness on new products and engaging Product PMs - Develop and execute change management strategies to drive end-user adoption and maximize value within customer organizations, including Train the Trainer programs, Center of Excellence development, and organizational enablement - Ruthlessly prioritize across the account's many business units and workstreams, building programmatic, repeatable motions You may be a good fit if you have: - 6+ years of experience in Customer Success, Technical Account Management, Solutions Engineering, or Strategy Consulting - Native English and Spanish - Experience working with F500 technology companies, SaaS platforms, or digital-first businesses at the exec level—ideally including high-growth and established tech companies. - You understand what it means to lead organization-wide change or adoption programs (multiple functions, hundreds of users) for a product that requires C-suite sponsorship - Technical fluency with ability to understand and articulate AI/ML concepts, API integrations, and software implementation patterns across a set of diverse stakeholders—from developers and product managers to executives and end users - Proven track record managing a portfolio of accounts while maintaining strong relationships and driving measurable outcomes — you can run multiple enterprise motions in parallel without letting any account go quiet. - Cross-functional collaborator who represents the customer in a positive, proactive manner, rallying everyone around paths forward that solve customer needs - Passion for AI and interest in responsible development of advanced systems. You have built with Claude Code, automating your own workflows with agents, skills, and tooling. - A knack for bringing order to chaos and an enthusiastic "roll up your sleeves" mentality The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $200,000 - $265,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

A

Head of ASEAN, Applied AI

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As the founding leader of Applied AI Solutions Architecture in Singapore, you will drive the adoption of frontier AI by enabling the deployment of Anthropic's products (Claude for Enterprise, Claude Code, and API) across ASEAN enterprises and digital-first organizations. You'll leverage your technical skills and consultative sales experience to drive positive AI transformation that addresses our customers' business needs, meets their technical requirements, and provides a high degree of reliability and safety. You'll be responsible for building and leading the ASEAN Applied AI team from the ground up. Applied AI comprises Solutions Architects, Product Engineers, and Finetuning Engineers. You will establish processes and best practices for the region's technical pre-sales engagements based on your years of experience, help each team member achieve success, high productivity, and career growth, and represent Anthropic as a technical lead on some of its most important partnerships across ASEAN. In collaboration with the Sales, Product, and Engineering teams globally and locally, you'll help enterprise partners across ASEAN incorporate leading-edge AI systems into their cutting-edge products and platforms. You will employ your excellent communication skills to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike. You will play a critical role in identifying opportunities to innovate and differentiate our AI systems, while maintaining our best-in-class safety standards. Responsibilities - Build and manage the foundational team of Applied AI professionals in ASEAN regions (Solutions Architects and Product Engineers) providing both technical guidance and career development - Set goals and reviews for your team, promoting growth and output - Work with a handful of highest-value enterprise customers across ASEAN on their overall AI adoption strategies, focusing on pre-sales technical excellence including use case scoping, technical champion building, and POC execution - Partner closely with your aligned GTM leadership to understand customer requirements & co-build GTM strategies to drive adoption for ASEAN enterprise customers - Contribute to thought leadership through conference presentations, webinars, and technical content creation within the ASEAN market - Own the technical portions of pre-sales engagements, ensuring your team provides compelling demos and validates enterprise customer ROI from Anthropic products - Drive collaboration from cross-functional teams to influence and unify stakeholders at all levels of the organization to drive business outcomes - Travel regularly to customer sites across ASEAN for executive-level sessions, technical workshops, and building relationships - Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products - Lead the vision, strategy, and execution of innovative solutions that leverage our latest models' capabilities - Stay current with emerging AI/ML trends and competitive landscape in the ASEAN enterprise tech sector, including the region's highly regulated industries (financial services, government, resources) You may be a good fit if you have - 15+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role - 5+ years of technical go-to-market management experience, specifically managing pre-sales teams - Experience working with ASEAN enterprise customers and understanding local business culture, procurement processes, and decision-making dynamics across ASEAN - Familiarity with the ASEAN regulatory landscape (e.g., Singapore Privacy Principles, APRA CPS 234, data sovereignty requirements) and how it impacts enterprise AI deployments - Experience with the unique technical requirements and technical procurement process of enterprise tech companies - Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases - Have an organizational mindset and enjoy building foundational teams in a relatively unstructured environment - Have excellent communication, collaboration, and coaching abilities - Are comfortable dealing with highly uncertain, ambiguous, and fast-moving environments typical of the tech industry - Strong executive presence and ability to foster deep relationships with technical leaders and engineering teams - Have at least a high level familiarity with the architecture and operation of large language models and/or ML in general - Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems - Make ambiguous problems clear and identify core principles that can translate across scenarios - Have a passion for making powerful technology safe and societally beneficial - Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks - Stay up-to-date and informed by taking an active interest in emerging research and industry trends - Understanding of developer tooling, SDKs, and technical integration patterns common in enterprise tech companies Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

C

Forward Deployed Engineer, Agentic Platform (Korea...

Negotiable

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! About North North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. Why This Role? This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. We’re looking for senior software engineers with Applied AI experience who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs), from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows. You’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one. What You’ll Do Customer-Facing Technical Impact - Work closely with enterprise customers to translate high-value, ambiguous business problems into well-framed agentic problems with clear success criteria and evaluation methodologies. - Provide technical leadership across the full development and evaluation lifecycle, including post-deployment iteration, for agentic workflows. - Travel up to 20–40% to work on-site with customers and partners Agent Design, Build and Production launches - Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools and data sources with enterprise-grade reliability and performance. - Balance rapid iteration with enterprise requirements, evolving prototypes into stable, reusable solutions. - Define and apply evaluation and quality standards to measure success, failures, and regressions; Debug real-world agent behavior and systematically improve prompts, workflows, tools, and guardrails. - Build and ship features for North, our AI workspace platform, working across the full product lifecycle from conceptualisation through production - Take ownership of scoping and shaping use cases end-to-end, flexing into whatever technical area the problem demands (including frontend) to drive the most effective solution Team Mentorship & Organizational Impact - Mentor engineers across distributed teams. - Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization. - Contribute to shared frameworks and patterns that enable consistent delivery across customers. Required Skills & Experience Technical Foundations - Demonstrated ability to build, ship, and operate production-grade software systems. - Substantial hands-on experience designing, building, evaluating, and fine-tuning LLM-based agents in real-world applications. - Deep familiarity with modern LLM ecosystems, including models (e.g., GPT, Claude, Gemini), vector databases, RAG architectures, agent/orchestration frameworks, prompt engineering, tool use, multi-step agent workflows (e.g., ReAct), and robust failure handling. - Strong proficiency in Python and/or JavaScript/TypeScript. Experience and Leadership - Experience working directly with customers or stakeholders to design and deliver LLM-powered agentic solutions aligned with real business needs. - Proven technical leadership at the team level, including guiding architecture, implementation, and delivery of complex AI systems. Additional Requirements - Strong written and verbal communication skills. - Fluency in English and Korean language. It’s a bonus if you have: - Experience setting architectural standards for AI and agentic systems across distributed teams - Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it - Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms) - Experience with enterprise security, compliance, or auditability requirements for AI systems Full-Time Employees at Cohere enjoy these Perks: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. How and Where We Work: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form , and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers page.

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Applied Scientist - Research Engineer (Tabular Dat...

Negotiable

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role Mistral AI is seeking Applied Scientists and Research Engineers focused on tabular data. You will design, train, and deploy SOTA models that understand, query, and reason over structured data, and apply them to diverse use cases. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions. We are made of researchers, engineers, product builders, ex-founders who love tackling the most complex real world problems in the industry. What you will do - Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. - Generate and curate datasets of tables, spreadsheets and databases, and build evaluators and benchmarks for table understanding, text-to-SQL, and prediction on tabular data. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. About you - Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences. - Expert with PyTorch or JAX. - Experience training or fine-tuning large language models, or tabular foundation models (e.g. TabPFN). - Strong background in machine learning on tabular data, including classical baselines (e.g. gradient boosting), and comfortable with SQL, pandas, and messy real-world data. - Not afraid of contributing to a big codebase; finds their way around independently with little guidance. - Writes clean, readable, high-performance, fault-tolerant Python code. - Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. Nice to have - Ex-founder or builder - PhD / Master in a relevant field (Computer Science, Statistics, Machine Learning) — exceptional candidates from other backgrounds welcome. - Experience with text-to-SQL, table question answering, or spreadsheet agents. - Experience with reinforcement learning using verifiable rewards (e.g. query execution). - Experience working on large code bases or large machine learning models at scale. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

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Applied Scientist - Research Engineer (Optimisatio...

Negotiable

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role Mistral AI is seeking Applied Scientists and Research Engineers focused on optimisation and operational research. You will post-train SOTA large language models to formulate and solve optimisation problems, and apply them to diverse use cases. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions. We are made of researchers, engineers, product builders, ex-founders who love tackling the most complex real world problems in the industry. What you will do - Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. - Generate and curate datasets for optimisation modelling (LP, MILP, constraint programming, scheduling, routing), and build evaluators and benchmarks for operational research tasks. - Use solvers as verifiers to build reward signals for reinforcement learning. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. About you - Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences. - Expert with PyTorch or JAX. - Experience training or fine-tuning large language models for reasoning, code, or mathematics. - Strong background in operational research or mathematical optimisation, with hands-on experience using solvers (e.g. Gurobi, CPLEX, OR-Tools) and modelling languages (e.g. Pyomo, AMPL). - Not afraid of contributing to a big codebase; finds their way around independently with little guidance. - Writes clean, readable, high-performance, fault-tolerant Python code. - Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. Nice to have - Ex-founder or builder - PhD / Master in a relevant field (Operational Research, Applied Mathematics, Machine Learning) — exceptional candidates from other backgrounds welcome. - Experience with reinforcement learning using verifiable rewards. - Experience with LLM-based optimisation modelling (e.g. NL4Opt-style problem formulation). - Industry experience in supply chain, logistics, energy, or scheduling. - Experience working on large code bases or large machine learning models at scale. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

F

Member of Technical Staff, Research (2026 PhD New...

$200,000 – $300,000

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE: This role is designed for researchers finishing their PhD who want their work to reach production, not just publication. As a Member of Technical Staff on the Research team, you'll push the boundaries of generative AI, advancing LLMs and multimodal systems through foundational research. Your work will enhance model efficiency, accuracy, and scalability, directly shaping our high-performance AI infrastructure. You'll be paired with a senior researcher as a mentor and given a real research problem from day one. You'll collaborate with top experts in deep learning, distributed systems, and optimization, and you'll see the models you help create deployed by some of the world's leading companies — often within weeks rather than years. We welcome candidates who have completed within the last 6 months, or expected completion by December 2026. KEY RESPONSIBILITIES - Conduct foundational research to advance the capabilities, efficiency, and reliability of LLMs and multimodal systems - Design, implement, and evaluate novel model architectures, training methods, and optimization techniques - Work alongside engineering teams to transition research prototypes into production-grade systems - Analyze empirical results, identify performance bottlenecks, and iterate quickly to improve model quality - Bring ideas and emerging directions from your doctoral research into our internal research agenda MINIMUM QUALIFICATIONS: - PhD completed within the last 6 months, or expected completion by December 2026, in Computer Science, Machine Learning, Computational Physics, Mathematics, Electrical Engineering, or a similar field - Research background in Artificial Intelligence, Machine Learning, Physics, or a related area, demonstrated through your dissertation, publications, or research projects - Experience solving analytical problems using analytic and quantitative approaches - Experience communicating research to audiences with different backgrounds - Proficiency coding in Python, C/C++, or other similar languages - Hands-on experience with ML frameworks such as PyTorch, JAX, or TensorFlow PREFERRED QUALIFICATIONS: - First-authored publications at top-tier peer-reviewed conferences or journals (NeurIPS, ICML, ICLR, MLSys, or similar) - Industry research internships, or open-source contributions to ML systems, model training, or inference projects - Research or engineering experience demonstrated via grants, fellowships, patents, or coding competitions - Experience with large-scale model training, distributed systems, GPU kernel development, or inference optimization - Experience taking research code beyond the prototype stage Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

O

Machine Learning Data Scientist - Consumer Forecas...

$347,000 – $445,000

About the Team The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more. We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential. About the Role We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability. This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains. - Own the end-to-end modeling lifecycle , including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability. - Develop and productionize scalable, interpretable forecasts for user growth, monetization, compute load, customer lifetime value, and profitability. - Contribute to self-service forecasting tools and internal platforms , enabling teams across OpenAI to access and act on real-time predictions. - Research and evaluate emerging tools and techniques in the forecasting space, such as TimeGPT, large language model extensions, causal forecasting, and hybrid approaches. - Drive strategic insight generation by translating technical outputs into business-aligned recommendations and decision frameworks. - Collaborate closely with cross-functional teams to ensure forecasts are well-integrated into planning processes, experimentation workflows, and executive decision-making. You might thrive in this role if you have: - Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research). - 7+ years of experience in applied data science, with deep hands-on exposure to forecasting, predictive modeling, or marketplace systems. - Expertise in time-series forecasting techniques and practical understanding of model trade-offs across performance, explainability, and scalability. - Proficiency in Python , SQL , and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries. - Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments. - Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders. - Self-directed, intellectually curious, and comfortable leading ambiguous projects from 0→1. Bonus if you have: - Experience building or scaling forecasting platforms in a high-growth company. - Familiarity with causal inference, Bayesian forecasting. - Experience building agentic decision support systems. - Passion for AI and a strong point of view on how machine learning should inform strategic decisions in fast-moving environments. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.