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Enterprise Account Executive (Australia)
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 an experienced Account Executive to join our growing GTM team and drive the next wave of growth at LangChain. In this role, you’ll own the full sales cycle helping technical teams at cutting-edge enterprise companies discover, evaluate, and adopt LangChain’s products. This is a high-impact, high-visibility role where you’ll collaborate closely with engineering, product, and customer success teams to shape how GenAI is adopted across different domains. If you're a relationship-driven seller who thrives in fast-paced, unstructured environments and wants to be part of building the go-to-market motion from the ground up, we’d love to hear from you. WHAT YOU’LL DO - Own and manage the full sales cycle, from lead stage to close with a strong bias for follow-up and follow-through - Act as a trusted advisor to prospects and customers, learning their needs and demonstrating how our products can solve real problems - Drive proof-of-concept efforts, working with sales engineers and product experts to demonstrate tangible value - Stay on top of product updates and industry trends to educate customers and shape the conversation around GenAI adoption - Build long-term customer relationships and support post-sale success in partnership with our deployment and support teams - Negotiate pricing and deal terms and work with legal to redline contracts - Bring customer insights back to product and engineering teams to inform the future roadmap and improve the user experience - Help define and iterate on our sales playbook - your input will help shape our go to market strategies WHAT YOU WILL BRING - 5+ years of experience selling complex software to enterprise customers - A relationship builder that garners trust quickly and approaches sales with empathy and curiosity - Excellent communication and storytelling skills - Technical acumen with the ability to establish credibility with technical decision makers. - You thrive in fast-paced start-up environments and are energized by impact - you want to help evolve the playbook, not just follow one - Driven and solutions-oriented; you know how to navigate roadblocks and keep deals moving forward - Passionate about generative AI and excited to help customers navigate a rapidly evolving industry Compensation - Annual salary range: $225,000-$350,000 OTE USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Enterprise Account Executive (Atlanta)
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 LangChain 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. Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500. 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. About the role: We’re looking for an experienced Account Executive to join our growing GTM team and drive the next wave of growth at LangChain. In this role, you’ll own the full sales cycle helping technical teams at cutting-edge enterprise companies discover, evaluate, and adopt LangChain’s products. This is a high-impact, high-visibility role where you’ll collaborate closely with engineering, product, and customer success teams to shape how GenAI is adopted across different domains. If you're a relationship-driven seller who thrives in fast-paced, unstructured environments and wants to be part of building the go-to-market motion from the ground up, we’d love to hear from you. Location: - Atlanta WHAT YOU’LL DO: - Own and manage the full sales cycle, from lead stage to close with a strong bias for follow-up and follow-through - Act as a trusted advisor to prospects and customers, learning their needs and demonstrating how our products can solve real problems - Drive proof-of-concept efforts, working with sales engineers and product experts to demonstrate tangible value - Stay on top of product updates and industry trends to educate customers and shape the conversation around GenAI adoption - Build long-term customer relationships and support post-sale success in partnership with our deployment and support teams - Negotiate pricing and deal terms and work with legal to redline contracts - Bring customer insights back to product and engineering teams to inform the future roadmap and improve the user experience - Help define and iterate on our sales playbook - your input will help shape our go to market strategies How to be successful in this role: - 5+ years of experience selling complex software to enterprise customers - A relationship builder that garners trust quickly and approaches sales with empathy and curiosity - Excellent communication and storytelling skills - Technical acumen with the ability to establish credibility with technical decision makers. - You thrive in fast-paced start-up environments and are energized by impact - you want to help evolve the playbook, not just follow one - Driven and solutions-oriented; you know how to navigate roadblocks and keep deals moving forward - Passionate about generative AI and excited to help customers navigate a rapidly evolving industry Compensation & Benefits: - We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. - Annual salary: $350,000 OTE USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Education Marketing Lead
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 Location: San Francisco, CA or New York City, NY LangChain Academy is how developers, engineers, and AI practitioners go from curious to capable on LangChain's products. We're looking for an Education Marketing Lead to own the strategy and execution that turns LangChain Academy into a meaningful growth channel for LangChain at large. This is a high-ownership role sitting at the intersection of education and growth. You'll build the programs, systems, and go-to-market motions that drive Academy enrollment at scale, while shaping the learner experience that keeps developers coming back and advancing through our curriculum. You'll work with the Technical Content Manager and across education engineers, deployed engineers, brand design, lifecycle marketing, and our SEO agency. LangChain already has strong technical credibility and a developer community that cares deeply about building with our products. Education is one of the highest-leverage ways to deepen that relationship and expand our reach. Your job is to build the marketing engine that makes LangChain Academy a destination for agent engineers. WHAT YOU'LL DO Marketing Academy - Drive enrollment. Develop and execute promotional campaigns that reach developers where they are, within LangChain docs, on social, through the newsletter, and via community touchpoints, to consistently drive top-of-funnel course enrollment. - Build and scale certification programs. Own the development and launch of LangChain Academy certification offerings, from program design and credentialing mechanics to marketing and positioning that makes them worth earning. - Drive organic discovery through SEO. Partner with our SEO agency to own search strategy for Academy landing pages and educational content. Ensure courses and tutorials are positioned to capture high-intent developer search traffic and continuously improve organic reach over time. - Lead end-to-end course launches. Own the go-to-market process for every LangChain Academy course, from launch planning and cross-functional coordination to promotional execution across docs, socials, the LangChain website, email, and community channels. - Own LangChain Academy's external presence. Manage and continuously improve the Academy landing pages and external-facing site. Learner Lifecycle & Engagement - Invest in email and nurture flows for enrolled learners. Partnering with lifecycle marketing to build and optimize onboarding sequences, course completion nudges, and flows that keep learners progressing and guide them toward their next course or certification. - Collaborate with the Technical Content Manager on pathways and bundles. Work closely with the Education Manager to develop and market curriculum pathways and course bundles that help learners understand how to progress through the Academy and make it easy to take the next step. - Optimize for enrollment and engagement. Take a growth mindset to the learner funnel. Understand where learners drop off and make data-informed decisions about how to fix issues. Partnerships & Community - Build educational distribution partnerships. Identify and develop co-marketing and distribution opportunities with learning platforms (LinkedIn Learning, DataCamp, and similar) and AI/ML communities that can expand Academy's reach to the right audiences at scale. - Think systemically about developer onboarding through education. Be the person always asking: how do we use education to get more developers successfully building on LangChain? Bring ideas, run experiments, and build programs that move the needle on product adoption through learning. - Own the YouTube education content calendar. Maintain and drive the content calendar for education-focused YouTube videos and tutorials, working closely with education engineers and deployed engineers to plan, schedule, and promote content consistently. Measurement & Reporting - Own top-of-funnel enrollment numbers. You're accountable for Academy enrollment as a metric. Always have a point of view on what's driving it, what's holding it back, and what to do next. - Track what matters beyond enrollment. Work with the Technical Content Manager to analyze reporting on learner engagement, course completion rates, drop-off, NPS, and content performance across Academy and YouTube. Use the data to inform what gets made, how it gets promoted, and where the experience needs work. WHAT WE'RE LOOKING FOR - Systems thinker with a growth mindset. You're organized and process-oriented. You can own a CMS, run a content calendar, and manage a launch, but you're always thinking about what would move the number and how to test it. - Developer empathy. You understand what earns trust with technical audiences. You know the difference between educational content developers find genuinely useful and content that feels like a tutorial-shaped ad. - Strong communicator and writer. You can write crisp promotional copy, a clear course description, and a launch brief, and you have a POV on tone that feels credible and human, not corporate. - Collaborative operator. You're comfortable working across the Technical Content Manager, education engineers, deployed engineers, lifecycle marketing, brand design, and an external SEO agency, synthesizing different inputs into a coherent plan and owning execution. - Technical curiosity. Genuine interest in AI and the developer ecosystem. Familiarity with LangChain products or similar tools is a strong plus. You'll need to understand what we build and who we build it for in order to market it well. NICE TO HAVE - Experience marketing developer education, online courses, or technical content programs - Familiarity with LMS or course CMS platforms (we use Thinkific) - Experience building or launching certification or credentialing programs - Background in developer marketing - Experience with YouTube content strategy and growth for technical audiences - Prior experience working with an SEO agency or owning organic search strategy for a content-heavy site Salary Range: $160,000 - $210,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (UK)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Stockholm)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (South EMEA)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos - Native French Speaker NICE TO HAVE’S - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Seattle)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 5+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $165,000–$380,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Salt Lake City)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires up to 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION & BENEFITS We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Annual OTE range: $155,000–$360,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Raleigh)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $150,000–$250,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Phoenix)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires up to 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $155,000–$360,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Las Vegas)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires up to 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $155,000–$360,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Germany)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Denver)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires up to 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $155,000–$360,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Charlotte)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $150,000–$250,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Atlanta)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $150,000–$250,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Deployed Engineer (Amsterdam)
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 TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Customer Marketing Manager
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 Customer Marketing Manager to own how our customers' stories show up in the market. Our customers are building some of the most interesting agent systems in production today — and the best version of our marketing is them, in their own words, talking about what they built and why it matters. You'll own the full customer storytelling motion end-to-end: sourcing the right customers, running the interviews, producing the case studies, videos, and talks, and turning those stories into assets that move pipeline, close deals, and shape the narrative around agent engineering. You'll also build the programs that sit underneath the stories — references, advocacy, customer councils, launch participation — so that by the time we need a customer voice for a launch, an analyst briefing, or an enterprise deal, we already have the right relationships in place. This is a builder role. We have remarkable customer logos and real production stories to tell, but the customer marketing function itself is early. You'll help define what it looks like at LangChain. WHAT YOU’LL DO: - Own the customer story pipeline end-to-end. Source customers, run the interviews, draft the narrative, and ship in multiple formats, including written case studies, videos, executive spotlights, conference talks, and podcasts. - Build the reference and advocacy programs. You’ll equip sales with a relevant reference for any deal, and our best customers with a clear path to speak, write, and represent LangChain in the market. - Get customers into our biggest moments. Product launches, events, analyst briefings, keynote stages, and press moments. You'll work with PMM to identify which customers belong in which moments, and you'll handle activation end-to-end. - Turn customer stories into pipeline. Partner with sales to use customer stories where they can move deals, including talk tracks, account-specific reference matches, customer-led webinars, and proof points that help technical champions sell internally. - Partner with field and community marketing to develop customer events and programs that build community. Founder dinners, customer roundtables, executive meetups, and hands-on workshops with our most engaged builders. - Build the voice-of-customer feedback loop. Synthesize what you hear in customer conversations into clear input for product, PMM, and comms. You'll be one of the people in the company who hears the most directly from the people building on us. - Measure what matters. Customer-influenced pipeline, references delivered, stories produced, advocacy participation. Build the muscle for measuring this from the start. WHAT YOU’LL BRING: - You have 4-6+ years in customer marketing, product marketing, or customer-led content marketing, with a track record of owning the customer story motion end-to-end. - You've built reference, advocacy, or customer-champion programs from scratch, or rebuilt one that wasn't working. You can point to programs that are still running and references that sales actually uses. - You're a strong writer. You can take a one-hour interview with a senior engineer and turn it into a story that a technical buyer wants to read and an executive wants to forward. - You're comfortable with technical customers. Our customers are engineers and AI/ML teams building agents in production. You can follow a conversation about agent architectures, evals, or deployment patterns, ask good questions, and translate what you hear for both technical and executive audiences. - You ship. You'd rather get a strong story out the door this week and iterate than spend a month on the perfect case study. You have a bias toward volume and momentum without losing the bar on quality. - You're a good partner across functions. Customer marketing only works if sales, PMM, comms, product, and CS all want to work with you. You bring people along. - You have a genuine curiosity about what customers are building with agents. The best customer marketing in this space comes from people who actually find the work interesting. - You use AI tools in your own workflow and you're always looking for new ways to increase your effectiveness with them. NICE TO HAVE: - Experience marketing developer tools, AI/ML infrastructure, or other technical platforms where the customer is an engineer or technical leader. - Experience with launch motions, including early access programs, beta cohorts, and getting the right customers into the right launch moments. - Comfort with multi-format production: video shoots, podcast prep, conference talk coaching, executive spotlights. - Familiarity with the LLM/agent developer ecosystem. - Experience working with both startup and enterprise customer segments, and an instinct for how to tell a story that resonates with each. WHY JOIN: - Our customers are shipping transformational agents to production at leading startups and enterprises. You’ll get to tell stories about people and agents that are changing industries. - Your work will directly impact the business. Customer stories drive deals, references close them, and advocacy builds company brand. This is a role where the impact is visible and measurable. - Agents are where software is heading. LangChain is at the center of that, and you'll shape how the story gets told to the teams building them. - Real scope on a growing team. You're joining a small team that's scaling fast. You'll help build the playbook for customer marketing here. - You’ll join a team that ships. We move fast, hold the bar high, and don't wait for layers of approval. COMPENSATION - Location: San Francisco, CA (strong preference) - Annual salary: $160,000 - 180,000 + equity Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Content Lead
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. Location: San Francisco, CA, New York, NY, or Remote We're looking for a Content Lead to build and scale LangChain's content practice. In this player/coach role, you'll drive our strategic content direction while managing and mentoring a Content Marketer. You'll lead the vision for how we reach, educate, and deepen engagement with our developer community—from blog and thought leadership to flagship initiatives. Beyond execution, you'll build the processes, standards, and team capabilities that allow us to produce high-quality, high-velocity content as we scale. This is a high-impact role with real ownership. You'll shape LangChain's voice in the developer community and set the editorial bar for technical quality. You'll stay hands-on with our most critical content initiatives while empowering your team to own end-to-end projects. You'll partner closely with education, engineering, product, and marketing to surface the most important stories and ensure our work reaches the right audiences through the right channels. You should be comfortable moving between big-picture strategy and hands-on execution—deciding what we publish and why, while also writing and editing key pieces and iterating on quality. You'll define our editorial direction and content roadmap, build scalable workflows and standards, mentor your team on both craft and strategy, own flagship projects like the State of Agents report, and collaborate with our SEO agency on SEO efforts. WHAT YOU'LL DO Build and mentor your content team: Hire, onboard, and develop a high-performing Content Marketing team. Provide regular feedback, coach them toward strategic thinking, delegate ownership of key initiatives, and create growth opportunities. Set clear expectations, establish editorial standards, and empower your team to ship great content independently. Define content strategy and roadmap: Develop and execute the strategic vision for LangChain's content, identifying key themes, audience segments, and content opportunities that drive business goals. Create a rolling editorial calendar that aligns with product launches, market moments, and developer needs. Lead flagship content initiatives: Drive industry-defining thought leadership pieces like the State of Agents report. Work with internal subject matter experts to produce authoritative, data-driven content that shapes industry conversation. Own blog performance and organic growth: Drive organic web traffic through exceptional content strategy and execution. Own blog metrics including traffic, engagement, and conversion. Work with your team to ideate, execute, and iterate on content that resonates with developers. Write and edit high-impact content: Create and edit strategic blog posts, thought leadership pieces, and long-form content. Stay hands-on with our most important pieces to maintain voice, quality, and technical accuracy. Model excellent writing and editing for your team. Expand SEO & AEO investments: Strengthen our SEO program by collaborating with our SEO agency to shape strategy, identify high-impact opportunities, and prioritize content initiatives. Work with your team to implement SEO best practices across all output. Set content quality standards and build scalable systems: Establish and evolve editorial guidelines, voice standards, and quality frameworks. Create content processes and workflows that enable high-quality, high-velocity output without sacrificing rigor. Enable your team to work efficiently while maintaining excellence. Enable cross-functional content creation: Lead partnerships across education, engineering, and marketing. Develop content frameworks and workflows that empower other teams to create high-quality strategic content. Source technical expertise and translate complex ideas into clear narratives. Measure impact and optimize: Define success metrics, track content performance across channels, and use data to refine strategy. Share insights and recommendations with leadership and cross-functional partners to improve reach, engagement, and conversion. WHAT WE'RE LOOKING FOR Experience: Experience in content marketing, editorial, product marketing, or related roles at developer-focused or technical product companies. 1+ years of managing or mentoring individual contributors preferred. Track record of building and scaling content functions. Leadership and mentorship: Natural ability to develop people. You give thoughtful feedback, delegate with clarity, and help teammates grow into more strategic, independent contributors. You set high standards and model the behavior you expect. Exceptional writing and editing: Outstanding ability to write clear, compelling, technically accurate content for developer audiences. Strong editorial judgment, attention to detail, and a distinctive point of view on what makes content great. Strategic thinking: Ability to see the big picture—how content serves business goals and drives adoption. You think in terms of content systems, not just individual pieces. You prioritize ruthlessly based on impact. SEO expertise: Proven track record of driving organic traffic growth through SEO-optimized content. Experience working with SEO tools and agencies to implement successful strategies. Technical acumen: Ability to understand and communicate complex technical concepts to developer audiences. Bonus if you're familiar with LangChain, LangSmith, and/or AI/ML concepts. Data-driven mindset: Strong analytical skills with experience tracking content metrics, A/B testing, and using insights to optimize strategy and prove ROI. Cross-functional collaboration: Excellent communication and partnership skills. You work effectively with engineering, education, product, and marketing teams. You're comfortable advocating for your vision while staying flexible. Ownership mentality: You're a self-starter who thrives in ambiguity, takes initiative, and drives results with minimal direction. You care deeply about developer satisfaction and community impact. Builder mentality: You're scrappy and hands-on. You're willing to do what it takes to ship great content, iterate quickly, and systematize as you scale. Point of view on AI: Thoughtful perspective on where AI enhances the content creation process and where human judgment is essential for quality and authenticity. Salary range: $210,000 - $220,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. 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.
Technical Program Manager, AI Infrastructure
About the Role We’re hiring a Technical Program Manager, AI Infrastructure to lead high-impact programs that power Character.AI http://Character.AI’s model development and serving systems at scale. In this role, you’ll partner closely with engineering, research, and product teams to shape infrastructure strategy, align roadmaps, and drive end-to-end execution for critical initiatives across training, evaluation, and inference. You’ll help ensure our systems are reliable, efficient, and capable of supporting rapid iteration as we scale AI experiences to millions of users. This role is a good match for someone who thrives in technically complex environments, enjoys bringing structure to ambiguous problem spaces, and can drive alignment across deeply cross-functional teams. You’ll often operate at the intersection of research and production, helping teams navigate tradeoffs between speed, quality, and reliability. You should be comfortable influencing without authority, anticipating risks early, and keeping large, interdependent efforts moving forward. What You’ll Do - Lead planning and execution of major AI infrastructure initiatives spanning training pipelines, data systems, model evaluation, and inference/serving - Build structures that keep teams aligned: scopes, goals, requirements, timelines, risks, and success metrics - Partner with engineering, research, and product to translate model and product needs into infrastructure roadmaps and priorities - Drive cross-functional accountability and communication across teams working on tightly coupled systems - Track key infrastructure metrics (e.g., reliability, latency, throughput, cost efficiency) and define reporting that surfaces progress and risk - Identify bottlenecks in infrastructure workflows and lead efforts to improve tooling, automation, and developer velocity - Support capacity planning and resource allocation to ensure infrastructure scales with model and product growth - Develop repeatable frameworks and operational patterns that improve execution quality across infrastructure programs - Serve as a strategic partner to leaders on prioritization, sequencing, and tradeoffs across infrastructure investments. - Work closely with AI cloud providers and serve as the primary bridge between internal engineering teams and external partnership efforts. - Technical understanding of GPU clusters, AI accelerator chips, and cloud providers to effectively evaluate requirements and guide infrastructure decisions. What You’ll Bring - 5–8 years of experience in program management, technical operations, or product execution in a fast-moving, technical environment - Proven ability to lead complex, multi-team initiatives spanning engineering and infrastructure systems - Strong communication skills with the ability to bridge technical and non-technical stakeholders - Experience working closely with engineering teams on distributed systems, cloud infrastructure, or platform development - Ability to break down ambiguous problem spaces into clear plans and drive alignment across teams - Analytical mindset with experience using data to inform decisions and measure impact - Strong ownership and execution mindset, with the ability to manage multiple priorities simultaneously ABOUT CHARACTER.AI Character.AI http://Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI http://Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventures. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year—a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI! At Character, we value diversity and welcome applicants from all backgrounds. As an equal opportunity employer, we firmly uphold a non-discrimination policy based on race, religion, national origin, gender, sexual orientation, age, veteran status, or disability. Your unique perspectives are vital to our success.
TPU Kernel Engineer
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 TPU Kernel Engineer, you'll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimizing kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance. Strong candidates will have a track record of solving large-scale systems problems and low-level optimization. You may be a good fit if you: - Have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators - Are results-oriented, with a bias towards flexibility and impact - Pick up slack, even if it goes outside your job description - Enjoy pair programming (we love to pair!) - Want to learn more about machine learning research - Care about the societal impacts of your work Strong candidates may also have experience with: - High performance, large-scale ML systems - Designing and implementing kernels for TPUs or other ML accelerators - Understanding accelerators at a deep level, e.g. a background in computer architecture - ML framework internals - Language modeling with transformers Representative projects: - Implement low-latency, high-throughput sampling for large language models - Adapt existing models for low-precision inference - Build quantitative models of system performance - Design and implement custom collective communication algorithms - Debug kernel performance at the assembly level 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: $280,000 - $850,000 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.
Technical Specialist, Claude Code
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 hiring Technical Architects: hands-on builders and live technical communicators who help our customers go from "we bought Claude" to "our people use it every day." You'll be the technical partner our CSMs pull into the room whenever the work gets technical — and at our customers, that's most of the time. One week you're running a Claude Code hackathon for 1000 engineers at a global bank. The next you're on a call with their CISO walking through data handling, SSO, and governance controls. The week after, you're pair-building a plugin with a customer's platform team and debugging a SCIM sync live while thirty people watch. You are the helper people look for. We're looking for technologists who could have been researchers or staff engineers, but who get the most energy from helping other people get unstuck and teaching them something real along the way. What you'll do - Be the technical lead in customer-facing moments across the post-sale journey: onboarding workshops, developer hackathons, live troubleshooting, executive security reviews, adoption working sessions. - Build and ship working software — Claude Code plugins, agents, sub-agents, MCP integrations, Cowork skills — both as customer deliverables and as reusable field assets. - Own enterprise deployment and identity conversations: SSO (SAML/OIDC), SCIM provisioning, role and seat management, sandbox and permission design. Sit credibly across from CISOs and security architects. - Advise and unblock customers running production workloads on the Anthropic API and on Bedrock / Vertex, in close partnership with Applied AI. - Teach — design and deliver enablement that turns provisioned seats into daily active developers, for audiences ranging from senior staff engineers to business users new to AI. - Partner tightly with CSMs as their technical counterpart, and with Applied AI, Product Support, Engineering, and Sales as the connective technical tissue of the account. What we're looking for - You build. You've shipped real software, you've used Claude Code or comparable AI coding tools yourself, and you can stand behind your engineering choices. - You hold the room. You're at ease being the technical voice in front of senior developers, IT and security leaders, and non-technical stakeholders — often in the same hour — and you stay calm and useful when something breaks live. - You like the messy middle. You'd rather be pulled into an ambiguous customer situation and figure it out than own a clean, narrow lane. - You're service-oriented. Helping a colleague or a customer get unstuck is the part of the day you look forward to. What you'll learn - How Claude is served. We'll teach you the service delivery side of Anthropic — how inference runs behind the API and Claude Code, and what drives capacity, latency, and reliability — so you can walk a customer's engineering and security teams through it at whatever depth the conversation and our agreements allow. You don't need this knowledge coming in; you do need the curiosity to go get it. Nice to have - Hands-on depth with enterprise identity (SAML, OIDC, SCIM) and security review processes. - Experience running on or supporting Bedrock / Vertex / multi-cloud LLM deployments. - A track record of public technical communication — talks, workshops, courses, writing. - Time spent in a post-sales, support, implementation, or technical account role. 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: £180,000 - £225,000 GBP 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.
Technical Program Manager, Safeguards (Infrastruct...
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 Safeguards Engineering builds and operates the infrastructure that keeps Anthropic's AI systems safe in production — the classifiers, detection pipelines, evaluation platforms, and monitoring systems that sit between our models and the real world. That infrastructure needs to be not just correct, but reliable : when a safety-critical pipeline goes down or degrades, the consequences can be serious, and they can be invisible until someone looks closely. As a Technical Program Manager for Safeguards Infrastructure and Evals, you'll own the operational health and forward momentum of this stack. Your primary responsibility is driving reliability — owning the incident-response and post-mortem process, ensuring SLOs are defined and met in partnership with various teams, and making sure that when things go wrong, the right people know, the right actions get taken, and those actions actually get closed out. Alongside that ongoing operational rhythm, you'll coordinate the larger platform investments: migrations, eval-platform improvements, and the cross-team dependencies that connect them. This role sits at the intersection of operations and program management. It requires genuine technical depth — you need to understand how these systems work well enough to triage effectively, judge what's actually safety-critical versus what can wait, and have informed conversations with the engineers building and maintaining them. But the core of the job is keeping the machine running well and the work moving. What You'll Do: - Own the Safeguards Engineering ops review - Drive the recurring cadence that keeps the team informed and coordinated: surfacing recent incidents and failures, bringing visibility to reliability trends, and making sure the right people are in the room when decisions need to be made. This is the heartbeat of how Safeguards Eng stays ahead of operational risk. - Drive incident tracking and post-mortem execution - When incidents happen — and in this space, they happen regularly — you'll make sure they get followed through properly. That means tracking incidents across the organization (including those owned by partner teams like Inference), ensuring post-mortems get written, and most critically, making sure the action items that come out of them actually get done. Closing the loop on post-mortem actions is one of the highest-leverage things this role does. - Establish and maintain SLOs with partner teams - Work with Safeguards Engineering teams and key partners — particularly Inference and Cloud Inference — to define service-level objectives for safety-critical pipelines. Then build the tracking and reporting that makes it possible to tell whether those SLOs are being met, and surface it when they're not. - Maintain runbook quality and incident-ownership clarity - Safety-critical systems need clear playbooks for when things go wrong. Partner with engineering leads to keep runbooks accurate, actionable, and up to date — and ensure that ownership of incidents (including for areas like account-banning false positives and CSAM detection) is unambiguous so that nothing falls through the cracks during an active incident. - Drive platform migrations and infrastructure projects - Own the program management for the larger infrastructure work on the roadmap: migrating the infra from one platform to the next, moving from one incident platform to the next and from one cloud system monitoring to another, and other migrations as they come. These are cross-team efforts with real dependencies — your job is to keep them sequenced, on track, and connected to the teams that need them. - Coordinate evals platform improvements - Partner with the evals engineering team to drive improvements to the evaluation platform — including self-serve capabilities and the broader eval factory infrastructure. Help scope the work, track dependencies on other Safeguards systems, and make sure the evals platform is keeping pace with the team's needs. You might be a good fit if you: - Have solid technical program management experience, particularly in operational or infrastructure-heavy environments — you're comfortable owning a mix of ongoing operational cadences and discrete project work simultaneously. - Understand how production ML systems work well enough to triage incidents intelligently and have substantive conversations with engineers about what's going wrong and why — you don't need to write the code, but you need to follow the technical thread. - Are energized by closing loops. Post-mortem action items that never get done, SLOs that no one checks, runbooks that go stale — these things bother you, and you know how to build the processes and follow-ups that fix them. - Can work effectively across team boundaries — comfortable coordinating with partner teams (like Inference) where you don't have direct authority, and skilled at keeping shared work moving through influence and clear communication. - Thrive in environments where the work shifts between "keep the lights on" and "build something new" — and can context-switch between incident follow-ups and longer-horizon platform projects without dropping either. - Have experience with or strong interest in AI safety — you understand why the reliability of a safety-critical pipeline is a different kind of problem than the reliability of a product feature, and that distinction motivates you. Strong candidates may also: - Have experience with SRE practices, incident management frameworks, or on-call operations at scale. - Have worked on or with evaluation infrastructure for ML systems — understanding how evals get designed, run, and interpreted. - Have experience driving infrastructure migrations in complex, multi-team environments — particularly where the migration touches operational systems that can't go offline. - Be familiar with monitoring and alerting tooling (PagerDuty, Datadog, or equivalents) and the operational culture around them. Deadline to apply: None, applications will be received 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: $290,000 - $365,000 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.
Technical Program Manager, Compute
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 Technical Program Manager on the Compute team, you will help drive the planning, coordination, and execution of programs that keep Anthropic's compute infrastructure running efficiently at scale. Our compute fleet is the foundation on which every model training run, evaluation, and inference workload depends. You'll join a small, high-impact TPM team and take ownership of critical workstreams across the compute lifecycle, from how supply is procured and brought online, to how capacity is allocated and utilized across teams. The exact focus will depend on your strengths and the team's evolving needs. You'll partner with Infrastructure, Systems, Research, Finance, and Capacity Engineering to shape the processes, tooling, and coordination mechanisms that allow Anthropic to move fast while managing an increasingly complex compute environment. Responsibilities: - Own and drive critical programs across the compute lifecycle, coordinating execution across multiple engineering, research, and operations teams - Build and maintain operational visibility into the compute fleet, ensuring the organization has a clear picture of supply, demand, utilization, and health - Lead cross-functional coordination for compute transitions: bringing new capacity online, migrating workloads, and managing decommissions across cloud providers and hardware platforms - Partner with engineering and research leadership to navigate competing priorities and drive alignment on how compute resources are planned, allocated, and used - Identify and close operational gaps across the compute pipeline, whether through new tooling, improved processes, or better cross-team communication - Own trade-off discussions between utilization, cost, latency, and reliability, synthesizing inputs from technical and business stakeholders and communicating decisions to leadership - Develop and improve the processes and frameworks the team uses to plan, track, and execute compute programs at increasing scale and complexity You may be a good fit if you: - Have 7+ years of technical program management experience in infrastructure, platform engineering, or compute-intensive environments - Have led complex, cross-functional programs involving multiple engineering teams with competing priorities and ambiguous requirements - Have experience working with research or ML teams and translating their needs into operational plans and technical requirements - Are comfortable diving deep into technical details (cloud infrastructure, cluster management, job scheduling, resource orchestration) while maintaining program-level visibility - Thrive in ambiguous, fast-moving environments where you need to define scope and build processes from the ground up - Have strong communication skills and can engage credibly with engineers, researchers, finance, and executive leadership - Have a track record of building trust with engineering teams and driving changes through influence rather than authority Strong candidates may also have: - Experience managing compute capacity across multiple cloud providers (AWS, GCP, Azure) or hybrid cloud/on-premises environments - Familiarity with job scheduling, resource orchestration, or workload management systems (Kubernetes, Slurm, Borg, YARN, or custom schedulers) - Experience with GPU or accelerator infrastructure, including the unique challenges of large-scale ML training and inference workloads - Built or improved observability for infrastructure systems: dashboards, alerting, efficiency metrics, or cost attribution - Capacity planning experience including demand forecasting, cost modeling, or hardware lifecycle management - Scaled through hypergrowth in AI/ML, HPC, or large-scale cloud environments Deadline to Apply: None, applications will be received 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: $290,000 - $365,000 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.
Technical Cyber Threat Investigator
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 We are looking for a Technical Cyber Threat Investigator to join our Threat Intelligence team. In this role, you will be responsible for detecting, investigating, and disrupting the misuse of Anthropic's AI systems for malicious cyber operations. You will work at the intersection of AI safety and cybersecurity, conducting thorough investigations into potential misuse cases, developing novel detection techniques, and building robust defenses against emerging cyber threats in the rapidly evolving landscape of AI-enabled risks. Your work will directly protect the broader ecosystem from sophisticated threat actors who seek to leverage AI technology for harm. Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays. Responsibilities - Detect and investigate attempts to misuse Anthropic's AI systems for cyber operations, including influence operations, malware development, social engineering, and other adversarial activities - Develop abuse signals and tracking strategies to proactively detect sophisticated threat actors across our platform - Create actionable intelligence reports on new attack vectors, vulnerabilities, and threat actor TTPs targeting LLM systems - Conduct cross-platform threat analysis grounded in real threat actor behavior, using open-source research, dark web monitoring, and internal data - Utilize investigation findings to implement systematic improvements to our safety approach and mitigate harm at scale - Study trends internally and in the broader ecosystem to anticipate how AI systems could be misused, generating and publishing reports - Build and maintain relationships with external threat intelligence partners, information sharing communities, and government stakeholders - Work cross-functionally to build out our threat intelligence program, establishing processes, tools, and best practices You may be a good fit if you - Have demonstrated proficiency in SQL and Python for data analysis and threat detection - Have experience with large language models and understanding of how AI technology could be misused for cyber threats - Have subject matter expertise in abusive user behavior detection, such as influence operations, coordinated inauthentic behavior, or cyber threat intelligence - Have experience tracking threat actors across surface, deep, and dark web environments - Can derive insights from large datasets to make key decisions and recommendations - Have experience with threat actor profiling and utilizing threat intelligence frameworks (MITRE ATT&CK, etc.) - Have strong project management skills and ability to build processes from the ground up - Possess excellent communication skills to collaborate with cross-functional teams and present to leadership Strong candidates may also have - Experience working with government agencies or in regulated environments - Background in AI safety, machine learning security, or technology abuse investigation - Experience building and scaling threat detection systems or abuse monitoring programs - Active Top Secret security clearance 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: $230,000 - $290,000 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.
Staff+ Software Engineer, Full-stack
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 Product Engineering org is looking for experienced engineers with strong full-stack fundamentals to join one of teams owning our current or emergent products. You'll be a technical leader who thinks holistically about the consumer and/or enterprise end user experience - be that via Claude.ai , the Anthropic API, enterprise deployments, Claude Code, or mission-driven applications - and carry real end-to-end ownership. You'll partner with engineering managers, product leaders, designers, and researchers to understand new model capabilities and redefine what is possible for users in the world of LLMs - and how to build it. We’ll look to you to have a product-oriented mindset and input, own technical quality across the stack (performance, accessibility, reliability, and developer experience), scale your efforts to millions of users on a global scale, and carry genuine excitement about what AI makes possible. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. What you'll do: Developer Experience: You'll build the products and tools - console, SDKs, docs, and observability - that give developers the confidence to rely on Claude in their most critical applications. Our mission is to meet developers where they are and bring them closer to the ceiling of what's possible with our models and API. That means building trust through great platform fundamentals, inspiring developers to raise the bar in how they use Claude's capabilities, and accelerating the path to agentic development by designing for both human and AI developers. You'll work closely with teams across the Platform org to turn Claude's newest capabilities into experiences developers can actually pick up and run with - from first prompt to production agent. Beneficial Deployments: Beneficial Deployments Engineering brings Claude to organizations doing the most good with the fewest resources — nonprofits, schools, healthcare providers, researchers, and economic mobility programs.We're looking for a full-stack engineer to build the access programs, tooling, and product work that make frontier AI usable for teams that couldn't afford this capacity any other way. Vertical AI Products: Purpose-built experiences for specific industries where Claude can transform complex professional work. We're currently building for three verticals, with more to come: - Financial Services — analysts and bankers across investment banking, asset management, insurance, and corporate finance, building models, memos, and decks under deadline. We're building deeply integrated experiences inside the tools they already use — retrieval, analysis, and document generation that holds up to executive review. - Life Sciences — an agentic research platform for scientists: specialist agents for computational biology, literature review, and regulatory review, built on model capabilities we're investing in for biology and chemistry. Live with early customers and expanding fast. - Healthcare — spanning payer workflows like claims, prior authorization, and utilization management, as well as clinical applications. Work where accuracy isn't a feature, it's the whole product — and where compliance is part of the engineering. Enterprise AI Products: You'll work on the products that make Claude a daily-use tool for enterprise customers across industries – the connective tissue that lets Claude operate effectively across workflows. On this team you will systematically understand why Enterprise users aren't activating, what's blocking adoption, and building the capabilities to close those gaps.Some of our focuses are: - Extensibility — plugins, skills, connectors, and the MCP ecosystem that lets a company shape Claude around their specific workflows and distribute that work across teams. - Context — enterprise knowledge, organizational memory, and the retrieval layer that makes Claude genuinely aware of a company's people, documents, and workflows. A connected, contextual Claude is the difference between a general-purpose chatbot and a real coworker. - Proactivity — Cowork suggestions, workflow capture, ambient Claude inside the apps people already use. Moving from "Claude answers when asked" to "Claude notices what you need". Public Sector: Build products that deliver Claude to the U.S. federal & state governments and allied democracies — from FedRAMP environments to classified networks. We're a startup-minded team with huge surface area: we own Claude for Government, ship zero-to-one products into the most regulated environments in the world, and work directly with the agencies using them Enterprise Foundations: You'll build the systems large organizations require before they can adopt Claude at scale: identity and permissions, security and compliance controls, and the admin analytics that let them see how it's being used. This is the work that turns "we love the demo" into a signed enterprise deal.The role is part product, part platform. You'll work closely with Product and GTM to understand what our largest customers need, then build it once in a way that works across Claude.ai, Claude Code, and Cowork. Growth: Drive user acquisition, engagement, retention, and monetization through data-driven strategies and technical implementations. At Anthropic, we're not just building AI tools; we're reimagining how AI can enhance and expand its user base! As a member of the growth team, you will have a unique opportunity to shape our growth strategy. You will work with a cross-functional team of engineers, data scientists, marketers, and product managers to design, implement, and optimize growth initiatives that scale our AI-powered tools and maximize their impact. Marketplace: builds the platform that connects Claude-powered enterprise tools through technology partnerships and deeper customer relationships. We work closely with business development, sales, product, and GTM teams, creating the infrastructure that powers partner onboarding, customer storefronts, transaction and entitlement flows at scale. We're building the technical scaffolding for a new offering, tackling the challenges at the intersection of commercial motions, platform architecture, and partner integrations so that enterprises, platforms, and Anthropic can transact with confidence. Passport: We're building the identity and verification product layer that enables safe model launches as Claude's capabilities expand. This critical effort partners with Safeguards, Auth & Identity, Policy, and Product teams across API, Claude.ai , and third-party platforms as customers, creating the systems for KYC/KYB, trust grant issuance and inheritance, and end-user verification that flow across every Anthropic surface. We sit at the intersection of trust, compliance, and product velocity, delivering the verification primitives that let Anthropic ship advanced model capabilities to the right users at massive scale. You might be a good fit if you: - Have a minimum of 8 years of practical full-stack engineering experience, ideally with 2+ years operating at a Staff or equivalent technical leadership level - Have led the design and delivery of complex, consumer or B2B user-facing products across the full stack - Are a technical expert in modern frontend and backend development, with demonstrated depth in key languages and frameworks (ie. React, Typescript) - Take a product-focused approach to building solutions that are robust, scalable, and easy to use - Have worked in early start-up or otherwise fast moving, rapidly evolving environments, and have ideally built products from 0 to 1 Care deeply in investing in the mentorship and growth of your peers - Have successfully driven cross-team/cross-org organizational alignment to get impactful work shipped, and work with influence over authority - Have experience establishing engineering standards, component architectures, and development best practices - Thrive in fast-paced environments and can navigate ambiguity to deliver high-quality products Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, NJ, SEA, SF or the Bay Area given the current location of 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.
Solutions Architect, National Security
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 member of the National Security Policy team at Anthropic, you will work directly with our most strategic national security customers and partners to drive transformational AI adoption. You will leverage your technical skills to architect innovative solutions that address our customers' business needs, meet their technical requirements, and provide a high degree of reliability and safety. In collaboration with the Sales, Product, Research, and Engineering teams, you’ll help national security partners develop strategies and implementation plans to integrate leading-edge AI systems into their mission. You will employ your excellent communication skills to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike. You also will play a critical role in identifying opportunities to innovate and differentiate our AI systems, while maintaining our best-in-class safety standards. We expect our team members to operate autonomously, thrive under ambiguity, and represent Anthropic at the highest level in customer environments. Core Responsibilities: - Act as a primary technical advisor for senior government leaders and prospective National Security customers evaluating Claude. Demonstrate how Claude can support U.S. and democratic allies’ national security operations and address customer use cases through proofs of concept. Provide technical guidance on integration, deployment, and adoption best practices. - Partner closely with the policy team and sales account executives to understand customer requirements. Develop customized pilots and prototypes, as well as evaluation suites to make the case for customer adoption. - Drive technical decision making by partnering on optimal setup, architecture, and integration of Claude into the customer's existing infrastructure. Demonstrate solutions to technical roadblocks. - Act as the voice of our customers and a key collaborator with our Product and Research teams to ensure we are delivering critical capabilities to the National Security community. - Travel to customer sites for senior leader meetings, AI implementation, technical enablement, and building relationships. - Establish a shared vision for creating solutions that enable beneficial and safe AI - Lead the vision, strategy, and execution of innovative solutions that leverage our latest models’ capabilities. You may be a good fit if you have: - Active TS/SCI security clearance (required) - 2+ years of experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Platform Engineer within the National Security space - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include senior executives, engineering & IT teams, and more - Experience in the defense, technology, or cybersecurity industries - Experience designing novel and innovative solutions for technical platforms in a developing mission area - Strong technical aptitude to partner with engineers and strong proficiency in at least one programming language (Python preferred) - Understanding of and experience with LLM fundamentals - The ability to navigate and execute amidst ambiguity, and to flex into different domains based on the business problem at hand, finding simple, easy-to-understand solutions - 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: $270,000 - $345,000 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.
Staff+ Software Engineer, Safeguards Infrastructur...
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 We are looking for software engineers to help build the foundational pieces for safety, oversight and intervention mechanisms of our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and ensure user well-being. This role will focus on building systems to detect unwanted model behaviors and prevent disallowed use of models. You will apply your technical skills to uphold our principles of safety, transparency, and oversight. Responsibilities: - Develop the foundational systems which power Safeguards, including infrastructure for data storage and management, metric and evaluation systems, and tooling for human and agentic review. - Ensure the day-to-day running of Safeguards systems and hold a high operational bar which serves both safety and customers while reducing the amount of human intervention and oversight required. - Build robust and reliable multi-layered defenses for real-time improvement of safety mechanisms that work at scale You may be a good fit if you have: - Bachelor’s degree in Computer Science, Software Engineering or comparable professional experience - Proficiency in Python - Ability to work across the stack - Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders Strong candidates may also: - 7+ years of experience in a software engineering position - Have experience building trust and safety, anti-spam, fraud or abuse detection and mitigation mechanisms and interventions for AI/ML systems - Have experience building metrics and measurement systems or data and privacy management systems - Have worked closely with operational teams to build custom internal tooling - Be proficient in TypeScript or Rust - Have experience with Claude Code or similar agentic coding tools 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: £325,000 - £395,000 GBP 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.
Staff+ Software Engineer, Node Infra
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 Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major cloud providers and from datacenters custom-built for Anthropic, stand up and scale the clusters behind one of the industry's largest AI compute fleets, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic's frontier AI research. Key responsibilities - Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair - Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families - Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity - Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others - Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy - Establish and evolve operational excellence practices (incident response, postmortem culture, on-call) - Support the growth of engineers around you through technical mentorship and coaching Minimum qualifications - Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure) - Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform. - Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium) - Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems - Ability to build alignment across senior stakeholders and communicate effectively at all levels Preferred qualifications - 10+ years of software engineering experience, including time as a technical lead setting direction for a team - Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency - Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines - Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons - Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads. - Demonstrated ownership of production reliability for high-throughput, latency-sensitive systems - Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.) - Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software 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: $320,000 - $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.
Senior Software Engineer, Full-stack
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 Product Engineering org is looking for experienced engineers with strong full-stack fundamentals to join one of teams owning our current or emergent products. You'll be a technical leader who thinks holistically about the consumer and/or enterprise end user experience - be that via Claude.ai , the Anthropic API, enterprise deployments, Claude Code, or mission-driven applications - and carry real end-to-end ownership. You'll partner with engineering managers, product leaders, designers, and researchers to understand new model capabilities and redefine what is possible for users in the world of LLMs - and how to build it. We’ll look to you to have a product-oriented mindset and input, own technical quality across the stack (performance, accessibility, reliability, and developer experience), scale your efforts to millions of users on a global scale, and carry genuine excitement about what AI makes possible. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. What you'll do: Developer Experience: You'll build the products and tools - console, SDKs, docs, and observability - that give developers the confidence to rely on Claude in their most critical applications. Our mission is to meet developers where they are and bring them closer to the ceiling of what's possible with our models and API. That means building trust through great platform fundamentals, inspiring developers to raise the bar in how they use Claude's capabilities, and accelerating the path to agentic development by designing for both human and AI developers. You'll work closely with teams across the Platform org to turn Claude's newest capabilities into experiences developers can actually pick up and run with - from first prompt to production agent. Beneficial Deployments: Beneficial Deployments Engineering brings Claude to organizations doing the most good with the fewest resources — nonprofits, schools, healthcare providers, researchers, and economic mobility programs.We're looking for a full-stack engineer to build the access programs, tooling, and product work that make frontier AI usable for teams that couldn't afford this capacity any other way. Vertical AI Products: Purpose-built experiences for specific industries where Claude can transform complex professional work. We're currently building for three verticals, with more to come: - Financial Services — analysts and bankers across investment banking, asset management, insurance, and corporate finance, building models, memos, and decks under deadline. We're building deeply integrated experiences inside the tools they already use — retrieval, analysis, and document generation that holds up to executive review. - Life Sciences — an agentic research platform for scientists: specialist agents for computational biology, literature review, and regulatory review, built on model capabilities we're investing in for biology and chemistry. Live with early customers and expanding fast. - Healthcare — spanning payer workflows like claims, prior authorization, and utilization management, as well as clinical applications. Work where accuracy isn't a feature, it's the whole product — and where compliance is part of the engineering. Enterprise AI Products: You'll work on the products that make Claude a daily-use tool for enterprise customers across industries – the connective tissue that lets Claude operate effectively across workflows. On this team you will systematically understand why Enterprise users aren't activating, what's blocking adoption, and building the capabilities to close those gaps.Some of our focuses are: - Extensibility — plugins, skills, connectors, and the MCP ecosystem that lets a company shape Claude around their specific workflows and distribute that work across teams. - Context — enterprise knowledge, organizational memory, and the retrieval layer that makes Claude genuinely aware of a company's people, documents, and workflows. A connected, contextual Claude is the difference between a general-purpose chatbot and a real coworker. - Proactivity — Cowork suggestions, workflow capture, ambient Claude inside the apps people already use. Moving from "Claude answers when asked" to "Claude notices what you need". Public Sector: Build products that deliver Claude to the U.S. federal & state governments and allied democracies — from FedRAMP environments to classified networks. We're a startup-minded team with huge surface area: we own Claude for Government, ship zero-to-one products into the most regulated environments in the world, and work directly with the agencies using them. Enterprise Foundations: You'll build the systems large organizations require before they can adopt Claude at scale: identity and permissions, security and compliance controls, and the admin analytics that let them see how it's being used. This is the work that turns "we love the demo" into a signed enterprise deal.The role is part product, part platform. You'll work closely with Product and GTM to understand what our largest customers need, then build it once in a way that works across Claude.ai, Claude Code, and Cowork. Growth: Drive user acquisition, engagement, retention, and monetization through data-driven strategies and technical implementations. At Anthropic, we're not just building AI tools; we're reimagining how AI can enhance and expand its user base! As a member of the growth team, you will have a unique opportunity to shape our growth strategy. You will work with a cross-functional team of engineers, data scientists, marketers, and product managers to design, implement, and optimize growth initiatives that scale our AI-powered tools and maximize their impact. You might be a good fit if you: - Have a minimum of 6 years of practical full-stack engineering experience - Have led the design and delivery of complex, consumer or B2B user-facing products across the full stack - Are technically proficient in modern frontend and backend development, with demonstrated depth in key languages and frameworks (ie. React, Typescript) - Take a product-focused approach to building solutions that are robust, scalable, and easy to use - Have worked in early start-up or otherwise fast moving, rapidly evolving environments, and have ideally built products from 0 to 1 - Have successfully driven cross-team alignment to get impactful work shipped, and work with influence over authority - Have experience establishing engineering standards, component architectures, and development best practices - Thrive in fast-paced environments and can navigate ambiguity to deliver high-quality products Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of teams. 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 - $320,000 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.
Safeguards Policy Analyst, Fraud & Scams
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 Safeguards Policy Analyst focused on Fraud & Scams, you will be responsible for designing, building, and executing enforcement workflows that detect and mitigate fraud and scam-related harms on Anthropic's products. You will serve as the subject matter expert on fraud typologies, scam ecosystems, and the threat actors who perpetrate them — translating that expertise into durable and scalable policies. This role sits within the Integrity & Authenticity (I&A) team, You will function both as a policy owner, and work closely with threat investigative and enforcement teams. You will also develop the guidelines that power classifiers, and will be our point of content cross-functional workstreams. No two days will look the same. Important context: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a financial, psychological, or otherwise disturbing nature, including detailed fraud schemes and scam content. Responsibilities: Policy Design & Ownership - Draft, maintain, and iterate on Fraud & Scams policies governing Anthropic's products and APIs, with clarity for both model enforcement and human reviewers - Conduct regular structured policy reviews to identify gaps, ambiguities, and coverage failures, and lead the process to close them - Develop detailed threat models for fraud and scam vectors — including social engineering, financial fraud, impersonation scams, phishing, and AI-enabled fraud — and translate these into enforceable policy language - Stay current on the fraud and scam landscape, including emerging typologies, regulatory shifts, and threat actor tactics, techniques, and procedures (TTPs) Enforcement Strategy & Operations - Design and architect automated enforcement systems and human review workflows that scale effectively while maintaining high precision and recall - Review flagged content to drive enforcement decisions and surface policy improvements grounded in real-world cases - Define and manage precision/recall tradeoffs in enforcement, working with data science teams to continuously tune classifiers and detection signals - Build and maintain an effective feedback loop between threat intelligence, policy, and enforcement operations to ensure timely response to novel and evolving fraud threats Technical & Cross-functional Collaboration - Serve as the primary policy point of contact for ML and Engineering teams developing fraud detection classifiers, working to translate policy intent into technical artifacts and training signals - Partner with Product, Engineering, and Data Science teams to optimize detection models, automated enforcement pipelines, and tooling for fraud-specific policy violations - Collaborate with external researchers, law enforcement liaisons, and fraud SMEs to gather feedback on policy effectiveness and emerging risk areas Stakeholder Alignment & Education - Educate and align internal stakeholders — including Legal, Public Policy, and Go-to-Market teams — around Anthropic's fraud and scams policies and enforcement approach - Serve as an internal resource on fraud risk, briefing leadership and cross-functional partners as threats evolve - Contribute to Anthropic's external communications and policy documentation related to fraud and platform integrity where relevant You may be a good fit if you have experience: - Working as a Trust & Safety professional with a focused background in fraud, scams, or financial crime — particularly in a tech platform or AI context - Writing, iterating on, and managing operational policies for fraud or abuse prevention at scale - Threat modeling for fraud and scam ecosystems, including social engineering, romance scams, investment fraud, impersonation, and phishing - Identifying and articulating common fraud tactics (e.g., pig butchering, advance fee fraud, account takeover facilitation) and how they manifest on AI platforms - Using SQL or other data analysis tools to identify trends, measure enforcement efficacy, and surface policy gaps - Collaborating cross-functionally with Engineering, ML, Legal, and Policy teams on safety initiatives - Working with generative AI products, including writing effective prompts for content review and enforcement use cases - Thriving in a fast-paced, ambiguous environment where priorities shift and the threat landscape evolves rapidly Preferred Qualifications: - Experience at a major technology platform, financial institution, or fraud intelligence firm in a policy, operations, or investigative capacity - Familiarity with the generative AI risk landscape and how large language models can be exploited for fraud and social engineering - Background in threat intelligence, financial crimes compliance (AML/KYC), or law enforcement focused on cyber-enabled fraud - Demonstrated ability to develop and communicate policy positions to diverse stakeholders including legal counsel and executive leadership 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.
Research Operations, External Artifacts
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 publishes risk reports: long-form technical documents laying out our assessment of the most serious potential risks from our models in domains like CBRN, cyber operations, and AI autonomy, along with the evaluation results behind that assessment, the safeguards we've applied, and our reasoning for why a given model is safe to deploy under our Responsible Scaling Policy. Some risk reports are standalone periodic assessments; others are more targeted, produced when we release a specific frontier model. These are some of the most consequential documents we produce, and one of the main ways we hold ourselves publicly accountable for the safety claims we make. We're hiring a Research Operations Specialist to own risk report operations. You'll be embedded with safety and research teams through each report cycle: coordinating contributions from dozens of researchers, holding the schedule and the open-threads list, and making sure the document ships on time as a single, internally consistent whole. You'll also do substantive editorial work, turning evaluation results, threat models, and researcher notes into clear prose and pushing back when a safety argument doesn't hold together. Risk reports sit within a wider family of external safety artifacts, including system cards and Responsible Scaling Policy updates. Part of this role is keeping those documents consistent with each other so that what we commit to in one place matches what we commit to and deliver on everywhere else. This role sits in Research Operations and works closely with our Frontier Red Team, Safeguards, Alignment, and capabilities researchers. The job is part project management, part translation: keeping a complex, many-author, hard-deadline document on track while making frontier risk assessment legible to researchers, policymakers, journalists, and the public without losing precision. Key responsibilities - Drive risk report production end to end: own the timeline, the contributor list, and the open-threads tracker - Coordinate core contributors across Frontier Red Team, Safeguards, Alignment, Interpretability, and capabilities research; chase drafts, resolve disagreements, find ground truth, and run the final polish pass - Edit (and sometimes write) content; work with researchers and red-teamers to turn evaluation results, threat models, and plots into clear, non-marketing prose, and keep Anthropic's voice consistent across sections drafted by many different people - Guard accuracy and consistency: catch terminology drift, risk claims that subtly contradict each other, and gaps between internal findings and what the draft says - Keep the risk report aligned with system cards, RSP disclosures, and other safety documentation, and flag conflicts early - Improve the process between reports; build templates, style guidance, and contributor checklists so each cycle starts from a stronger baseline - Pick up other research-adjacent operations and writing work related to our external artifacts and Anthropic's RSP Minimum qualifications - Demonstrated technical writing ability: can take dense, jargon-heavy source material and produce prose that is precise and readable by a smart non-specialist - Working conceptual knowledge of large language models, with fluency in terms like pretraining, RLHF, context windows, evals, red-teaming, and capability thresholds - Ability to read evaluation results tables, ask clarifying questions, and identify gaps in a technical argument - Track record of driving complex, multi-contributor projects to completion against hard deadlines Preferred qualifications - Strong project coordination instincts; experience managing many parallel open threads across contributors who are juggling other high-priority work - Ability to coordinate and influence without direct authority across research and engineering teams - An eye for data presentation; can assess whether a chart or table could be clearer or more accurate - Familiarity with AI safety, AI policy, alignment research, national security operations and/or policy, or threat modeling beyond baseline LLM knowledge - Experience with safety or compliance documentation: safety cases, risk assessments, security disclosures, or clinical/scientific reporting - Background in science communication, research publishing, or technical journalism - Track record of shipping long-form technical documents (research reports, whitepapers, standards, or regulatory filings) - Experience producing polished, visually consistent documents; an eye for layout and on-brand presentation - Comfort using frontier LLM tools as a productivity aid without substituting them for independent judgment 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: $260,000 - $310,000 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.
Research Engineer, RL Scaling Science
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 RL Scaling Science team studies how reinforcement learning behaves as we scale it (across model size, compute, and task horizon) and turns that understanding into the training recipes behind our frontier models. As a Research Engineer on this team, you'll design and run large-scale experiments to understand and resolve bottlenecks, build the benchmarks that make long-horizon progress measurable, and ship validated findings directly into production training. This role lives at the boundary between research and engineering. The problems are open, the experiments run at frontier scale, and the path from a robust result to production is short. Key responsibilities - Design, run, and interpret large-scale RL experiments, reasoning rigorously about what the data does and doesn't show - Investigate how RL improves as horizon, compute, and model size grow - Build and maintain benchmarks for long-horizon RL so progress is measurable and reproducible - Translate validated findings into production training recipes, exercising judgment about when a result is robust enough to ship - Debug complex issues at the seam where research meets infrastructure - failures that only appear at scale - Partner closely with adjacent RL teams across research and engineering and advance our overall RL stack Minimum qualifications - Strong empirical research skills in Reinforcement Learning, large-scale ML training, or a closely adjacent area - Demonstrated ability to own large experiments end-to-end, from design through interpretation - Proficiency in Python and experience working with large-scale or distributed ML systems - Comfort operating at the research/systems boundary, including debugging where the two meet - Care about the societal impacts of AI and responsible scaling Preferred qualifications - Published or shipped work in long-horizon RL or RL fundamentals - Experience translating research findings into production training recipes - Demonstrated large scale industry impact via RL interventions - Experience working on frontier-scale training runs with long trajectories Representative projects - Design a benchmark suite for long-horizon RL that distinguishes genuine capability gains from artifacts of evaluation setup - Take a promising experimental finding, stress-test it across model scales, and work with training teams to land it in a production recipe - Investigate an unexpected scaling trend in an RL run and trace it to a root cause spanning algorithm, data, and infrastructure 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: £375,000 - £640,000 GBP 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.
Regional Research Economist, Economic Research
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 Regional Research Economist at Anthropic, you will work to collaborate with governments, academia, industry, and civil society in your region to measure and understand AI's effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally-relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system ( Clio ), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. Key responsibilities - Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region - Advance research collaborations that answer country- or regional-specific economic impact questions - Translate research insights into actionable recommendations for policy discussions - Make fundamental contributions to the development and expansion of the Anthropic Economic Index , including country/regional-specific analysis - Design and collaborate on empirical research on AI's economic effects with governments, academia, industry, and civil society in your region - Develop new methodological approaches, in collaboration with partners in your region, for studying AI's impact on: - Labor markets and the future of work - Productivity and task transformation - Economic inequality and displacement - Industry-specific disruption and adaptation - Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios - Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection - Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders Minimum qualifications - PhD in Economics - Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning - Demonstrated experience working in and relevant relationships across the region - Experience relevant to the study of AI’s impact on the economy, including: - Labor market analysis and occupational change - Task-based approaches to technological transformation - Large-scale data analysis and econometric methods - Large language models for social science research - Policy-relevant economic research - Experimental and quasi-experimental methods for causal inference - Macroeconomic modeling and time series forecasting - Agent-based modeling or large-scale simulation - Technical skills including: - Proficiency in Python, R, SQL, or similar tools for large-scale data analysis - Experience working with novel datasets and measurement systems - Comfort learning new technical tools and frameworks - Demonstrated ability to: - Lead complex research projects from conception to publication - Communicate technical findings to diverse audiences - Build relationships across academic, policy, and industry communities - Strong interest in ensuring AI development benefits humanity - Comfort working with AI systems and ability to think critically about their capabilities and limitations Representative projects - How Australia Uses Claude: Findings from the Anthropic Economic Index - Anthropic Economic Index Report: Economic Primitives - Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption - Estimating AI productivity gains from Claude conversations - The Anthropic Economic Index Additional Information For this role, we're looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI's transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact. 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: £180,000 - £190,000 GBP 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.
Product Manager, Multi-Cloud Growth - Google
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 The Anthropic Platform Org’s mission is to help builders build. Our vision is to be the premier platform for businesses to transform themselves and their products with AI. This org is responsible for our APIs, self-serve developer experience, multi-cloud integrations, and agentic infrastructure. We serve a wide array of users from startups to large scale enterprises. The platform team is comprised of three key areas: - Enterprise fabric – where we are building multi-cloud integrations at extreme scale across our entire stack to meet businesses wherever they are and in the most demanding of requirements. - Frontier capabilities – where we are building developer experiences and features that enable users to get the most out of the model and build at the very frontier of intelligence. - Agentic platform – where we are inventing the next generation of agentic infrastructure for production-grade use and building new products to enable businesses to solve problems with agents. Responsibilities: Customer Understanding & Advocacy - Deeply engage with enterprise developers and technical leaders to understand their integration needs and pain points - Run regular feedback sessions and technical reviews with key enterprise customers - Build strong relationships with enterprise development teams to understand their workflows and challenges - Transform customer insights into actionable product requirements and priorities Product Strategy & Vision - Define and execute the enterprise API strategy, balancing security requirements with developer experience - Develop a clear roadmap for enterprise API features including authentication, rate limiting, and compliance capabilities - Identify and prioritize key enterprise integration patterns that drive organizational value Enterprise API Development - Partner with engineering to build enterprise-grade API features, security controls, and deployment tools - Design and implement enterprise integration frameworks and SDKs for common enterprise systems - Drive development of industry-specific API features and compliance capabilities Cross-functional Leadership - Partner with sales and customer success to understand enterprise requirements and support technical evaluations - Work closely with security and compliance teams to meet enterprise standards - Collaborate with platform teams on API architecture and scalability - Engage with marketing to develop enterprise API positioning and technical materials You may be a good fit if you: - Have 10+ years of experience in high-scale, high-reliability developer-facing software. - Have 5+ years of product management experience. - Have built or shipped products with a hyperscaler as a partner — you know how to align goals and deliver impact across that boundary. - Have owned a revenue number, a margin target, or a channel P&L — not just a product roadmap. - Operate with high autonomy in ambiguous, fast-moving environments. - Are an excellent written communicator and able to drive clarity out of complexity. - Excel at cross-company stakeholder management and can build trusted relationships at every layer of an organization. Strong candidates may also have: - Experience as a founder, GM, or early-stage operator where you owned commercial outcomes, not just product outputs. - Direct experience as a PM at AWS, GCP, or Azure — or at an ISV that ships through one of their marketplaces. 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: $305,000 - $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.
Product Engineer, Computer Use
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 The Computer Use team teaches Claude to see and operate computer interfaces, and builds the agent harness and end-user products that turn that capability into real tools. The team sits inside Anthropic's research organization and closes the loop between product and model. As a Product Engineer on this team, you'll own end-to-end delivery of our computer-use and browser-control product surfaces. You'll build across the full stack, from the user interface to the agent runtime to the backend services behind it. You'll work directly alongside researchers, with no layers between you and the model or the user. This is a dynamic role in which priorities evolve frequently. Success depends on a high tolerance for ambiguity, the adaptability to shift focus as needs change, and the agility and discernment to continuously prioritize the highest impact work. Key responsibilities - Own end-to-end delivery of computer-use and browser-control product surfaces: scope, build, ship, measure, and iterate - Diagnose and resolve reliability and robustness issues in the computer-use agent harness that block real-world usage - Partner with computer-use researchers - Partner with the Claude Cowork team on shared surfaces, integrations, and knowledge-worker workflows - Instrument products and use usage data to drive prioritization and measure progress - Translate fuzzy user pain points into concrete, shippable features for knowledge workers Minimum qualifications - Experience building and shipping a product from zero to one with end-to-end ownership, as a founding or early engineer at a startup or with equivalent ownership inside a larger company - Strong full-stack engineering skills, including production web frontend and backend development - Hands-on experience building with LLM APIs, prompting, or agent frameworks - A track record of shipping to external users and iterating based on their feedback Preferred qualifications - Strong product design instincts and the ability to produce a clean, usable interface without a dedicated designer - Experience with browser automation, desktop automation, or robotic process automation systems - Experience building evals or quality harnesses for machine learning systems - Comfort with lightweight data analysis, such as SQL, notebooks, and defining and tracking product metrics - Experience designing agent loops, tool integrations, or guardrails for LLM-based systems Representative projects - Own and resolve the top reliability and robustness issues on the computer-control and browser-control product surfaces, with measurable improvement in task success rate - Take a net-new computer-use powered workflow from concept to external users, including instrumentation and a readout on usage 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 - $320,000 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.
Policy Design Manager, Age-Appropriate Design
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 Safeguards Policy Design Manager, you will be responsible for developing usage policies, clarifying enforcement guidelines, and advising on safety interventions for our products and services. Your core focus will be on age-appropriate design and experiences, including child safety, age assurance, content classification, and adult sexual content. You will help define best practices for developers building on claude for deployment to users across different developmental stages, design age-assurance policies that protect minors from inappropriate content and interactions, and establish clear boundaries for adult content and experiences. In addition, you will advise teams on opportunities for age-appropriate helpfulness, including advising cross-functional teams on beneficial use cases for younger users where appropriate. Safety is core to our mission and you’ll help shape policy creation and development so that our users can safely interact with and build on top of our products in a harmless, helpful and honest way. *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. Responsibilities: - Serve as an internal subject matter expert, leveraging deep expertise in child safety, adult content, youth development, and age-appropriate design to: - Draft new policies that help govern the responsible use of our models for emerging capabilities and use cases - Design evaluation frameworks for testing model performance in areas of expertise - Conduct regular reviews and testing of existing policies to identify and address gaps and ambiguities - Review flagged content to drive enforcement and policy improvements - Update our usage policies based on feedback collected from external experts, our enforcement team, and edge cases that you will review - Work with safeguards product teams to identify and mitigate concerns, and collaborate on designing appropriate interventions for users across different age groups - Advise on age assurance approaches and content classification frameworks in partnership with Enforcement, Product, Engineering, and Legal teams - Educate and align internal stakeholders around our policies and our approach to safety in your focus area(s) - Keep up to date with new and existing AI policy norms, regulatory requirements (e.g., age-appropriate design codes), and industry standards, and use these to inform our decision-making on policy areas You may be a good fit if you have experience: - As a researcher, subject matter expert, or trust & safety professional working in one or more of the following focus areas: child safety, youth online safety, age assurance, developmental science, content classification and rating systems, or adult content policy. Note: For this role, an advanced degree in developmental psychology, child development, education, or a related field is preferred. - Drafting or updating product and / or user policies, with the ability to effectively bridge technical and policy discussions - Designing or implementing age-appropriate experiences, age assurance mechanisms, or content classification / labeling systems - Working with generative AI products, including writing effective prompts for policy evaluations and classifier development - Aligning product policy decisions between diverse sets of stakeholders, such as Product, Engineering, Public Policy, and Legal teams - Understanding the challenges that exist in developing and implementing product policies at scale, including in the content moderation space - Thinking creatively about the risks and benefits of new technologies, and leveraging data and research to inform policy recommendations - Navigating and prioritizing work efforts amidst ambiguity 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.
Performance Engineer, GPU
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: Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency. Working at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization. Strong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers. You might be a good fit if you: - Have deep experience with GPU programming and optimization at scale - Are impact-driven, passionate about delivering measurable performance breakthroughs - Can navigate complex systems from hardware interfaces to high-level ML frameworks - Enjoy collaborative problem-solving and pair programming - Want to work on state-of-the-art language models with real-world impact - Care about the societal impacts of your work - Thrive in ambiguous environments where you define the path forward Strong candidates may also have experience with: - GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization - ML Compilers & Frameworks: PyTorch/JAX internals, torch.compile, XLA, custom operators - Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight - Distributed Systems: NCCL, NVLink, collective communication, model parallelism - Low-Precision: INT8/FP8 quantization, mixed-precision techniques - Production Systems: Large-scale training infrastructure, fault tolerance, cluster orchestration Representative projects: - Co-design attention mechanisms and algorithms for next-generation hardware architectures - Develop custom kernels for emerging quantization formats and mixed-precision techniques - Design distributed communication strategies for multi-node GPU clusters - Optimize end-to-end training and inference pipelines for frontier language models - Build performance modeling frameworks to predict and optimize GPU utilization - Implement kernel fusion strategies to minimize memory bandwidth bottlenecks - Create resilient systems for planet-scale distributed training infrastructure - Profile and eliminate performance bottlenecks in production serving infrastructure - Partner with hardware vendors to influence future accelerator capabilities and software stacks Deadline to apply: None. Applications will be reviewed on a rolling basis. The expected salary range for this position is: 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: $280,000 - $850,000 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.
Performance Engineer
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: Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you'll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also. You may be a good fit if you: - Have significant software engineering or machine learning experience, particularly at supercomputing scale - Are results-oriented, with a bias towards flexibility and impact - Pick up slack, even if it goes outside your job description - Enjoy pair programming (we love to pair!) - Want to learn more about machine learning research - Care about the societal impacts of your work Strong candidates may also have experience with: - High performance, large-scale ML systems - GPU/Accelerator programming - ML framework internals - OS internals - Language modeling with transformers Representative projects: - Implement low-latency high-throughput sampling for large language models - Implement GPU kernels to adapt our models to low-precision inference - Write a custom load-balancing algorithm to optimize serving efficiency - Build quantitative models of system performance - Design and implement a fault-tolerant distributed system running with a complex network topology - Debug kernel-level network latency spikes in a containerized environment 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: $280,000 - $850,000 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.
Model Performance Software Engineer, Claude Code
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 We're looking for a Staff Software Engineer to set technical direction at the intersection of engineering and research on the Claude Code team. In this role, you'll partner directly with Anthropic's researchers and engineering leadership to shape how we measure, understand, and improve Claude's coding capabilities. You'll architect the systems, tooling, and evaluation infrastructure that determine how quickly our research can move—and you'll be accountable for the technical decisions that ripple across the team and beyond. This is a senior individual contributor role for someone who has already built and owned systems at significant scale, and who is ready to operate as a technical leader: driving architecture, mentoring engineers, and influencing the direction of Claude Code itself. Responsibilities - Set technical direction for evaluation systems, research infrastructure, and internal tooling across the Claude Code team - Architect eval frameworks that measure model capabilities across diverse coding tasks and scale with our research roadmap - Lead the design of infrastructure that enables researchers to run experiments at scale, and make the foundational tradeoffs that shape how the team operates for years - Identify the highest-leverage engineering investments—often before anyone has asked for them—and drive them to completion - Serve as a senior technical bridge between product and research, using strong product intuition to influence which capabilities we prioritize and how we measure progress against them - Mentor and raise the bar for other engineers on the team; review designs, unblock peers, and model the engineering standards we want to scale - Partner with research leads to translate ambiguous research questions into durable engineering solutions - Own critical systems end-to-end, from architecture through production reliability, and take responsibility for their long-term health You may be a good fit if you: - Have 10+ years of software engineering experience, with a track record of operating as a Staff or Principal engineer (or equivalent) at a high-caliber organization - Have architected and owned complex, high-stakes systems—pipelines, infrastructure, or platforms that orchestrate many components, handle significant state and logic, and serve multiple teams - Have a history of setting technical direction that others follow—through design docs, architectural decisions, or technical strategy that shaped how a team or org operates - Thrive in high-intensity environments with fast iteration cycles, and have the judgment to know when to move fast and when to invest in durability - Take full ownership of ambiguous, open-ended problems and drive them to completion with minimal direction - Are a power user of agentic coding tools with deep intuition about model capabilities and limitations - Can dive into unfamiliar technical domains—ML systems, research workflows, novel infrastructure—and get to the frontier quickly - Care deeply about correctness and reliability, and have raised engineering standards on teams you've been part of - Are energized by working at the boundary between engineering and AI research, and by the prospect of influencing both Strong candidates may also have experience with: - Designing or scaling eval/evaluation frameworks for ML systems - Reinforcement learning infrastructure or training systems - Leading technical initiatives in high-performance, demanding environments—trading firms, quant funds, frontier research labs, or fast-moving startups where intensity and technical excellence are the norm - Research computing, scientific infrastructure, or developer platforms at scale - A strong quantitative foundation (math, physics, or related fields) - Expertise in Python and TypeScript 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.
Manager, Account Executive - Strategic Sales
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 Sales Manager at Anthropic, you’ll lead a team of Strategic Account Executives driving the adoption of safe, frontier AI by securing strategic deals with top enterprises in the Telco, Media, and Retail verticals. You’ll leverage your leadership and consultative sales expertise to propel revenue growth while developing a high-performing team of AEs. Working closely with Applied AI Engineering and Product teams, you’ll help customers embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM and Marketing teams, you’ll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape. The ideal candidate will have a passion for developing people, identifying market opportunities, and executing strategies to capture them. By leading the deployment of Anthropic’s emerging products, you will help enterprises obtain new capabilities while also advancing the ethical development of AI. Key responsibilities: - Recruit, coach, and retain Strategic Account Executives with deep industry and platform-selling expertise; develop leadership talent and create career paths that keep top performers growing - Codify the use cases, proof points, reference stories, and sales motions that make wins repeatable within each industry, partnering with Marketing, Enablement, and partner teams to scale them - Engage personally with C-level executives on priority pursuits, building business cases and value narratives and navigating complex procurement, security, and legal processes through to production deployment and expansion - Own the organization's revenue targets and operating rhythm, instilling pipeline-generation discipline and running forecasting, deal inspection, and account planning cadences that make performance predictable and coachable across a high-volume book of business - Partner closely with Applied AI, Solutions Architecture, and Product to design solutions, prove value quickly, and translate industry needs into product and roadmap input - Orchestrate cross-functional and partner motions with Customer Success, Marketing, Partnerships, Legal, and cloud partners to deliver a seamless customer experience, and represent Anthropic with customers and at industry events as a visible, trusted leader Minimum qualifications: - Experience leading strategic sales teams that sell technical, complex products such as API-first platforms, cloud infrastructure, or data and machine learning platforms - A track record of winning and growing enterprise customers, including building C-suite relationships, in one or more of our focus industries (telecommunications, media & entertainment, retail & consumer, industrials & manufacturing, or business services) - Experience designing go-to-market coverage for a strategic sales team, including but not limited to account prioritization - Operational rigor across both a high-volume pipeline and complex, multi-stakeholder sales cycles, balancing velocity with deal quality and forecasting accurately in fast-changing environments - Credibility with technical buyers and builders — CIOs, CTOs, CDOs — and experience pairing effectively with solutions architects and applied AI teams - Strong coaching skills that raise team performance through deal coaching and account strategy, combined with personal effectiveness alongside executives on high-priority opportunities - A genuine interest in deploying AI responsibly and motivation to advance Anthropic's mission of building safe, beneficial AI Preferred qualifications: - Experience bringing generative AI or LLM-based products, or other emerging platform technologies, to enterprises in telco, media, or retail - Established executive relationships and a strategic-deal track record within the Telco, Media, or Retail verticals - Experience selling with and through cloud and ecosystem partners such as AWS, Google Cloud, and global systems integrators - Familiarity with consumption- or usage-based commercial models and value-based pricing conversations 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: $435,000 - $550,000 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.
Manager, Account Executive - GSIs
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 Sales Manager at Anthropic, you’ll lead a team of Strategic Account Executives driving the adoption of safe, frontier AI by winning and growing the world’s largest global systems integrators and consultancies — as both strategic customers and go-to-market partners. You’ll leverage your leadership and consultative sales expertise to propel revenue growth while developing a high-performing team of AEs. Working closely with Applied AI Engineering, Partnerships, and Product teams, you’ll help partners embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM and Marketing teams, you’ll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape. The ideal candidate will have a passion for developing people, identifying market opportunities, and executing strategies to capture them. By leading the deployment of Anthropic’s emerging products, you will help systems integrators and their clients obtain new capabilities while also advancing the ethical development of AI. Responsibilities: - Recruit, coach, and retain Strategic Account Executives with deep partner/alliance and platform-selling expertise; develop leadership talent and create career paths that keep top performers growing - Codify the use cases, proof points, reference stories, and sales motions that make wins repeatable across each GSI partner and across both the sell-to and co-sell motions, partnering with Marketing, Enablement, Partnerships, and the partners themselves to scale them - Engage personally with C-level executives at the GSIs — and, on co-sell pursuits, at their enterprise clients — building business cases and value narratives and navigating complex procurement, security, and legal processes through to production deployment and expansion - Own the organization's revenue targets and operating rhythm, instilling pipeline-generation discipline and running forecasting, deal inspection, and account planning cadences that make performance predictable and coachable across both the internal-adoption and co-sell pipeline - Partner closely with Applied AI, Solutions Architecture, and Product to design solutions, prove value quickly, and translate partner and client needs into product and roadmap input - Orchestrate cross-functional and partner motions with Customer Success, Marketing, Partnerships (PAMs), Legal, and cloud partners to deliver a seamless experience, and represent Anthropic with partners and at industry events as a visible, trusted leader You may be a good fit if you have: - Experience leading strategic sales teams that sell technical, complex products such as API-first platforms, cloud infrastructure, or data and machine learning platforms - A track record of winning and growing strategic customers and/or partners, including building C-suite relationships, ideally with global systems integrators, consultancies, or other large partner/alliance ecosystems - Experience designing go-to-market coverage for a strategic sales team, including account and partner prioritization - Operational rigor across both a high-volume pipeline and complex, multi-stakeholder sales cycles, balancing velocity with deal quality and forecasting accurately in fast-changing environments - Credibility with technical buyers and builders — CIOs, CTOs, CDOs — and experience pairing effectively with solutions architects and applied AI teams - Strong coaching skills that raise team performance through deal coaching and account strategy, combined with personal effectiveness alongside executives on high-priority opportunities - A genuine interest in deploying AI responsibly and motivation to advance Anthropic's mission of building safe, beneficial AI Strong candidates may have: - Experience bringing generative AI or LLM-based products, or other emerging platform technologies, to global systems integrators and consultancies, or to market through partner and alliance channels - Established executive relationships and a strategic-deal track record within global systems integrators or consultancies (e.g., Accenture, Deloitte, PwC, KPMG, EY, TCS, Infosys, Capgemini) - Experience running co-sell and build-with motions with global systems integrators and cloud partners such as AWS and Google Cloud - Familiarity with consumption- or usage-based commercial models and value-based pricing conversations 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: $450,000 - $550,000 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.
Manager of Applied AI Architecture, Enterprise Tec...
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 manager of the Solutions Architect team within Applied AI Enterprise Tech at Anthropic, you will drive the adoption of frontier AI in partnership with the rest of the go to market organization. Our Enterprise Tech customers are some of the world's most sophisticated technology companies, deploying AI at the core of their products and operations.. 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 will be responsible for leading and growing the pre-sales team that partners with account executives to help those companies understand and deploy Anthropic’s products, including Claude for Enterprise, Claude Code, and the API. This will include leveraging your technical skills and consultative sales experience to hire great people, establish processes for the team to scale, and represent Anthropic directly at strategic customer engagements. Responsibilities: - Hire, manage, and guide a team of pre-sales Solutions Architects by providing both technical guidance and career development. - Set goals for your team in collaboration with sales and other parts of the organization that establish baseline expectations for performance. - Act as a technical sponsor for high-value strategic customers and advise them on their overall AI adoption strategies or use case scoping and POC execution. - Partner closely with Enterprise Tech sales leadership to identify new strategies to drive adoption of Anthropic products across customer use cases. - Work with cross-functional teams like product and engineering to ensure Anthropic prioritizes customer feedback or resolves blockers to adoption. - Travel to customer sites 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/ML trends and the competitive landscape. You may be a good fit if you: - 7+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role. - 3+ years of technical pre-sales management experience. - 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 technical leaders and engineering teams at leading enterprise technology 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 10 to 50+ people), with direct experience managing senior individual contributors and developing junior talent in complex enterprise software sales environments. - 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-Segment GTM Experience : Demonstrated success adapting technical approaches across customer segments (commercial to Fortune 100). 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.
Head of Content & Curriculum, Education
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 AI capabilities are advancing faster than most people can adapt. The gap between what Claude can do and what people know how to do with it widens with every model release. Closing this gap before the window for thoughtful adoption narrows is core to our mission. The content & curriculum team sits at the heart of that mission. This isn’t docs, and it isn’t traditional courseware either. We’re building a library of educational content and experiences that can be delivered to each learner at the precise moment they need it, teach them effectively, and keep learning engaging. And we want to scale it with Claude (and, hopefully, you!) You'll own the education team’s content end to end—every audience (developers, consumers, enterprise admins, the general public) and every format (courses, tutorials, video, interactive experiences). Your obsession is the learner: does this actually empower people to use AI intentionally, is it the clearest version of itself, and are we proud of it? You'll manage a team of content strategists, plus the media designers, agencies, and agents who support them. Working hands-on with Claude is part of how content gets made here: you and your team will design the workflows and standards that determine where and how AI can accelerate drafting, review, and maintenance, and determine where human craft is non-negotiable os that the team so that the team can move faster without lowering the bar. Where that line sits, and how it moves as models improve, is yours to figure out. This isn't a traditional catalog you maintain. Models improve, audiences grow, and the best version of what you ship today won't be the best version six months from now. You’re building a content library that evolves in real time with Claude. Your goal is learning that adapts to each person and scales far past what any team could produce by hand, without ever giving up the quality bar that makes it worth learning from. The most exciting version of this role encodes its own craft into AI-powered systems rather than guarding it. Key responsibilities - Own the content and how well it teaches across every audience and format - Set and defend the quality bar for scaled education. Define what "great" means precisely enough that the team can hit it without you in the room - Push the medium forward: design learning that's beautiful, distinctive, interactive, and increasingly personalized, not templated courseware - Design and run the content production system (intake, prioritization, drafting, review, launch) at the cadence of model and product launches - Shape how Claude is used in production —the frameworks and standards that let AI accelerate output while keeping it excellent - Manage and develop the audience leads and media designers; play a key role in the education team’s growth and org design - Own learning measurement: how we know content is teaching, and how that feeds back into how we make it - Take us to the next stages of reach —localization, globalization, new audiences—and own the strategy and execution for getting there You might be a good fit if - You have genuine taste, and it's the first thing you bring. You can't walk past a clumsy explanation or a boring course. This matters more than anything else here - You've led a content, curriculum, or education function at scale, including managing leads, and you develop people as well as you do the craft - You’ve led teams through significant changes in pursuit of an audacious vision, and brought people along rather than leaving them behind - You build systems across many varied, cross-functional partners (product, engineering, marketing, design, agencies, subject matter experts) and coordinate them as one production engine rather than a chain of handoffs - You've produced learning across formats —written, video, interactive—and you know when to deploy each for maximum effect and efficiency - You've built and run technical curriculum before, and know what it takes to teach developers working in the field; at a minimum you can read code, you know what good looks like, and you can coach your technical team members through teaching complex topics - You're rigorous about measurement and grounded in learning science . You define what "working" means in a learning context, instrument for it, and act on what you find - You've produced content with Claude yourself, have real intuition for what to trust it with versus what still needs a human, and can continuously evaluate that line as models improve - You're energized by scaling your own craft . Encoding your taste into systems and workflows that produce far beyond what your own hands could genuinely excites you, and you embrace scaling the work with Claude rather than guarding it - You're comfortable that today's best content has a short shelf life, and you design for durability and fast regeneration rather than perfecting artifacts that models will outdate - You have a thesis about what teaching becomes when every learner has an adaptive AI tutor, and you're here to build that, not a better version of the old thing - You're a strong writer and editor who translates technical concepts without dumbing them down - Experience at a high-growth technology company (or somewhere with that pace) where product and audience considerations shift frequently, and often faster than plans do - You’re a collaboration magnet who is able to build strong relationships across many functions and teams in service of a single mission. Strong candidates may also have - Experience teaching advanced AI/ML topics to both technical and non-technical audiences - Experience building AI-assisted production workflows for content, media, or other creative work, and a point of view on where and how they break down and need human involvement and oversight - Experience designing interactive or adaptive learning products , such as tutoring systems, simulations, hands-on environments, not just linear courses What makes this role exciting - Define great teaching for the AI era . You'll set what it looks like in a world where AI is part of how content gets made - Pivotal moment, massive reach . Your work shapes how millions of people come to understand and use Claude and AI in general 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.
Global Indirect, Sales Tax & VAT
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 seeking an experienced Indirect Tax professional to join our Tax team. In this role, you'll be responsible for developing and executing our global indirect tax strategy across US sales tax and international VAT/GST. As we continue to scale our AI products globally, you'll play a critical role in ensuring tax compliance, optimizing our tax position, and building scalable systems and processes. You'll work cross-functionally with Finance, Accounting, Legal, Product, and Engineering teams to embed tax considerations into our business operations from the ground up. Responsibilities: - Develop and execute Anthropic's global indirect tax strategy for US sales tax and international VAT/GST across multiple jurisdictions - Assist with the end-to-end indirect tax compliance, including registration, filing, remittance, and audit defense - Partner with Product, Engineering, and GTM teams to assess the tax implications of new product launches, pricing models, and go-to-market strategies - Assist the business with identifying indirect tax requirements for all aspects of infrastructure projects and marketplace initiatives including implementation - Provide input into the evaluation, implementation, and administration of indirect tax technology solutions, including tax engines and compliance software - Design and implement scalable tax processes and internal controls to support rapid business growth - Lead nexus studies and taxability analyses to determine filing obligations across jurisdictions - Collaborate with external tax advisors and manage relationships with tax authorities - Monitor regulatory changes and assess their impact on Anthropic's business operations - Provide tax guidance on complex transactions and business arrangements - Prepare and review indirect tax provisions for financial reporting - Support internal and external audit requests related to indirect taxes You may be a good fit if you: - Have 8+ years of indirect tax experience, with deep expertise in US sales tax and international VAT/GST - Have experience in technology or SaaS companies, ideally with consumption-based or API business models - Possess strong technical knowledge of indirect tax rules, exemptions, and sourcing principles across multiple jurisdictions - Have hands-on experience implementing and managing tax technology solutions (e.g., Avalara, Vertex, Sovos, Taxjar) - Are proficient in analyzing complex business models and translating them into tax positions - Have excellent project management skills and can drive initiatives from concept to completion - Can clearly communicate complex tax concepts to non-tax stakeholders across all levels of the organization - Thrive in fast-paced, rapidly evolving environments and are comfortable with ambiguity - Have experience building processes and systems from the ground up in high-growth environments - Are detail-oriented with strong analytical and problem-solving abilities Strong candidates may also have: - BA, CPA, or other relevant professional certification - Experience with Oracle, Stripe, or similar billing and accounting platforms - Background in Big 4, national accounting firm or Industry indirect tax practices - Experience with AI/ML products or emerging technology taxation issues - Familiarity with tax automation and data analytics tools - Experience managing external advisors and audit processes 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: $230,000 - $300,000 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.
Engineering Manager, Research Productivity
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 Research Tools team builds systems that support our large-scale, distributed finetuning runs and improve the productivity of researchers. As a manager, you’ll support a team of machine learning and distributed systems experts to make these systems and tools highly efficient, support fast iteration on model development and research, and evolve the infrastructure continuously to incorporate new research advances. Our Research Tooling sits at the intersection of almost every technical group at Anthropic. You’ll work with research teams to incorporate their innovations into our production finetuning pipeline, product teams to help us iterate quickly on customer-oriented model improvements, and infrastructure teams to make sure our training runs and data pipelines are as efficient as possible. About Anthropic: Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and society as a whole. Our interdisciplinary team has experience across ML, physics, policy, business, and product. Responsibilities: - Prioritize the team’s work in collaboration with the technical lead, research teams, and product teams to support fast iteration on research projects and training runs. - Design processes (e.g., postmortem review, incident response, on-call rotations) that help the team operate effectively. - Coach and support your reports to understand and pursue their professional growth. - Run the team’s recruiting efforts efficiently, ensuring we can grow as quickly as we need through a period of rapid growth. You may be a good fit if you: - Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well. - Are an experienced manager (at least 2 years) and actively enjoy people management. - Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level) to be effective. Strong candidates may also have: - Experience working with research teams, especially as part of a “research to production” pipeline - Strong people management experience: Coaching, performance evaluation, mentorship, career development - Strong project management skills: Prioritization, communicating across team/org boundaries - Experience recruiting for your team: Predicting staffing needs, designing interview loops, evaluating candidates, and closing them 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: $405,000 - $850,000 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.
Engineering Manager, Inference
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 performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment. Responsibilities: - Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems - Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor - Manage day-to-day execution of the team's work - Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment - Coach and support your reports in understanding, and pursuing, their professional growth - Maintain a deep understanding of the team's technical work and its implications for AI safety You may be a good fit if you: - Have 1+ years of management experience in a technical environment, particularly performance or distributed systems - Have a background in machine learning, AI, or a similar related technical field - Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development - Excel at building strong relationships with stakeholders at all levels - Are a quick learner, capable of understanding and contributing to discussions on complex technical topics - Have experience managing teams through periods of rapid growth and change - Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective Strong candidates may also have experience with: - High performance, large-scale ML systems - GPU/Accelerator programming - ML framework internals - OS internals - Language modeling with transformers 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: $425,000 - $560,000 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.
Engineering Manager, GPU (ML Accelerator)
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 performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment. Responsibilities: - Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems - Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor - Manage day-to-day execution of the team's work - Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment - Coach and support your reports in understanding, and pursuing, their professional growth - Maintain a deep understanding of the team's technical work and its implications for AI safety You may be a good fit if you: - Have 1+ years of management experience in a technical environment, particularly performance or distributed systems - Have a background in machine learning, AI, or a similar related technical field - Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development - Excel at building strong relationships with stakeholders at all levels - Are a quick learner, capable of understanding and contributing to discussions on complex technical topics - Have experience managing teams through periods of rapid growth and change - Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective Strong candidates may also have experience with: - High performance, large-scale ML systems - GPU/Accelerator programming - ML framework internals - OS internals - Language modeling with transformers 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: $500,000 - $850,000 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.
Data Scientist, Marketing
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. Job Description As an early member of our Data Science team, you will play an instrumental role in our company's mission of building safe and beneficial artificial intelligence by aligning our marketing programs to benefit our customers, users and society. In this unique company, technology, and moment in history, your work will be critical to informing our marketing and personalization strategy as we deploy safe, frontier AI at scale to the world. You will work closely with marketing, product, and commercial teams to define and measure key success metrics and measurement approaches for our lifecycle and personalization efforts. You've worked in cultures of excellence in the past and are eager to apply that experience to building robust and scalable marketing analytics systems as our company continues through a period of rapid growth and evolution. Responsibilities : - Partner closely with marketing, product and commercial teams to understand our products and underlying user needs - Establish north star metrics and guardrails to understand the effectiveness of different marketing interventions - Develop a feedback approach which enables continuous learning and improvement for the teams operating in different marketing categories - Identify hypotheses on marketing initiatives, design experiments or causal inference studies, analyze the results, and make recommendations based on impact to key metrics - Build a data-driven marketing culture from the ground up by establishing foundational marketing analytics best practices and making marketing data more accessible across the company You might be a good fit if you have: - 6+ years of experience in data science or ML role, preferably in a marketing or customer acquisition context - 3+ years of experience deeply embedding in Marketing teams, turning marketing data into concise and insightful systems that drive business outcomes - A passion for the company's mission of building helpful, honest, and harmless AI - Experience building user segmentation systems to drive marketing campaigns - Experience with the ecosystem of Causal AI and related technologies - A bias for action and urgency, not letting perfect be the enemy of the effective - An ability to thrive and drive clarity in ambiguous, fast-moving environments 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: $285,000 - $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.
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