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About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Enterprise Account Executive at Anthropic, you'll join the foundational team at the forefront of introducing our cutting-edge AI productivity API and SaaS solutions to professional services firms across the EMEA markets. You'll drive the adoption of safe, frontier AI by securing strategic deals with consultancies, agency and marketing services groups, law firms, and accounting and advisory firms. You'll leverage your consultative sales expertise in the professional services sector to propel revenue growth while becoming a trusted partner to professional services stakeholders, helping them embed and deploy AI while uncovering its full range of capabilities in client delivery, research and analysis, and knowledge management. In collaboration with GTM, Product, and Marketing teams, you'll continuously refine our value proposition, sales methodology, and market positioning to resonate with professional services decision-makers. The ideal candidate will have a passion for developing new market segments, pinpointing high-potential opportunities, and executing strategies to capture them. By driving deployment of Anthropic's emerging products, you will help enterprises obtain new capabilities while also advancing the ethical development of AI. Responsibilities: - Win new business and drive revenue for Anthropic within the professional services sector. Navigate complex professional services firms to reach key decision-makers, educate them about our services, and help them succeed with Anthropic. You'll own the full sales cycle, from first outbound to close - Design and execute innovative sales strategies tailored to professional services procurement cycles, vendor risk assessment, and budgeting processes to meet and exceed revenue quotas. Analyse professional services market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities and campaigns - Spearhead market expansion by identifying new use cases within client delivery teams, creative and strategy functions, research and knowledge management, and business development. Collaborate cross-functionally to differentiate our offerings for professional services applications - Navigate complex professional services stakeholder ecosystems including executives, partners and practice leaders, IT departments, risk and compliance functions, and procurement offices to build consensus - Inform product roadmaps and features by gathering feedback from users and conveying professional services market needs. Provide insights that strengthen our value proposition for professional services - Continuously refine the professional services sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimise sales productivity and consistency You may be a good fit if you have: - 8+ years of B2B Enterprise sales experience in SaaS, API solutions, or emerging technologies - A track record of managing complex sales cycles within professional services firms and securing strategic deals by understanding both technical requirements and professional services use cases - Demonstrated ability to navigate professional services organisational structures and procurement processes, building consensus among diverse stakeholders including executives, partners and practice leaders, and IT departments - Extensive experience negotiating complex agreements within professional services procurement frameworks, vendor risk and third-party assurance policies - Proven experience exceeding revenue targets by effectively managing an evolving pipeline and sales process - Excellent communication skills and the ability to present confidently to various professional services audiences, from practice leads and delivery teams to senior partners - Deep understanding of professional services buying cycles, decision-making processes, and key pain points, including the client confidentiality and regulatory obligations firms operate within - A strategic, analytical approach to assessing the professional services market combined with creative, tactical execution to capture opportunities - A passion for and/or experience with advanced AI systems and their applications. You feel strongly about ensuring frontier AI systems are developed safely and ethically for professional services use 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 - £330,000 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.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Enterprise Account Executive at Anthropic, you'll join the foundational team at the forefront of introducing our cutting-edge AI productivity API and SaaS solutions to financial institutions across the EMEA markets. You'll drive the adoption of safe, frontier AI by securing strategic deals with banks, insurance companies, and financial research institutions. You'll leverage your consultative sales expertise in the financial services sector to propel revenue growth while becoming a trusted partner to financial stakeholders, helping them embed and deploy AI while uncovering its full range of capabilities in banking, research, and administration. In collaboration with GTM, Product, and Marketing teams, you'll continuously refine our value proposition, sales methodology, and market positioning to resonate with financial decision-makers. The ideal candidate will have a passion for developing new market segments, pinpointing high-potential opportunities, and executing strategies to capture them. By driving deployment of Anthropic's emerging products, you will help enterprises obtain new capabilities while also advancing the ethical development of AI. Responsibilities: - Win new business and drive revenue for Anthropic within the financial services sector. Navigate complex financial institutions to reach key decision-makers, educate them about our services, and help them succeed with Anthropic. You'll own the full sales cycle, from first outbound to close - Design and execute innovative sales strategies tailored to financial services procurement cycles and budgeting processes to meet and exceed revenue quotas. Analyze financial market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities and campaigns - Spearhead market expansion by identifying new use cases within financial departments, research centers, and administrative offices. Collaborate cross-functionally to differentiate our offerings for financial applications - Navigate complex financial stakeholder ecosystems including executives, administrators, IT departments, and procurement offices to build consensus - Inform product roadmaps and features by gathering feedback from financial users and conveying financial market needs. Provide insights that strengthen our value proposition for financial services - Continuously refine the financial services sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency You may be a good fit if you have: - 12+ years of B2B sales experience in financial services technology in SaaS, API solutions, or emerging technologies - A track record of managing complex sales cycles within financial institutions and securing strategic deals by understanding both technical requirements and financial use cases - Demonstrated ability to navigate financial bureaucracies and procurement processes, building consensus among diverse stakeholders including executives, administrators, and IT departments - Extensive experience negotiating complex agreements within financial services procurement frameworks and policies - Proven experience exceeding revenue targets in the financial services sector by effectively managing an evolving pipeline and sales process - Excellent communication skills and the ability to present confidently to various financial audiences, from analysts and researchers to senior executives - Deep understanding of financial services buying cycles, decision-making processes, and key pain points - A strategic, analytical approach to assessing the financial services market combined with creative, tactical execution to capture opportunities - A passion for and/or experience with advanced AI systems and their applications in financial services. You feel strongly about ensuring frontier AI systems are developed safely and ethically for financial use À propos du poste En tant qu'Enterprise Account Executive chez Anthropic, vous rejoindrez l'équipe fondatrice chargée de faire découvrir notre API de productivité IA de pointe et nos solutions SaaS aux institutions financières des marchés EMEA. Vous favoriserez l'adoption d'une IA de pointe et sûre en concluant des contrats stratégiques avec des banques, des compagnies d'assurance et des instituts de recherche financière. Vous mettrez à profit votre expertise de la vente consultative dans les services financiers pour accélérer la croissance du chiffre d'affaires. Vous nouerez aussi des relations de confiance avec les parties prenantes du secteur financier et les aiderez à intégrer et à déployer l'IA, tout en leur faisant découvrir l'étendue de ses capacités dans la banque, la recherche et l'administration. En collaboration avec les équipes GTM, Produit et Marketing, vous affinerez en continu notre proposition de valeur, notre méthodologie de vente et notre positionnement, afin qu'ils trouvent un écho auprès des instances décisionnelles du secteur financier. Le profil idéal a à cœur de développer de nouveaux segments de marché, de repérer les opportunités à fort potentiel et de mettre en œuvre les stratégies qui permettent de les saisir. En favorisant le déploiement des produits émergents d'Anthropic, vous aiderez les entreprises à acquérir de nouvelles capacités tout en contribuant au développement éthique de l'IA. Responsabilités : - Remporter de nouveaux contrats et générer du chiffre d'affaires pour Anthropic dans le secteur des services financiers. Vous orienter au sein d'institutions financières complexes pour atteindre les personnes décisionnaires clés, leur présenter nos services et les aider à réussir avec Anthropic. Vous piloterez l'intégralité du cycle de vente, de la première prise de contact à la signature. - Concevoir et mettre en œuvre des stratégies commerciales innovantes, adaptées aux cycles d'achat et aux processus budgétaires des services financiers, afin d'atteindre et de dépasser les objectifs de chiffre d'affaires. Analyser le paysage, les tendances et les dynamiques des marchés financiers pour traduire les plans stratégiques en actions et campagnes commerciales ciblées. - Piloter l'expansion sur le marché en identifiant de nouveaux cas d'usage au sein des directions financières, des centres de recherche et des services administratifs. Collaborer de manière transverse pour différencier nos offres destinées aux applications financières. - Naviguer dans des écosystèmes complexes de parties prenantes (direction générale, services administratifs, DSI et services achats) afin de construire un consensus. - Contribuer à la feuille de route et aux fonctionnalités produit en recueillant les retours des équipes utilisatrices du secteur financier et en relayant les besoins du marché. Apporter des éclairages qui renforcent notre proposition de valeur pour les services financiers. - Affiner en continu la méthodologie de vente dédiée aux services financiers en intégrant les enseignements dans des playbooks, des modèles et des bonnes pratiques. Identifier des améliorations de processus qui optimisent la productivité et la cohérence commerciales. Ce poste pourrait vous correspondre si vous avez : - Au moins 12 ans d'expérience en vente B2B dans les technologies pour les services financiers (SaaS, solutions API ou technologies émergentes) - Une solide expérience de la gestion de cycles de vente complexes au sein d'institutions financières et de la conclusion de contrats stratégiques, fondée sur une compréhension fine des exigences techniques comme des cas d'usage financiers - Une capacité avérée à naviguer dans les structures bureaucratiques et les processus d'achat du secteur financier, en construisant un consensus entre des parties prenantes variées, dont la direction, les services administratifs et les DSI - Une vaste expérience de la négociation d'accords complexes dans le cadre des politiques et procédures d'achat des services financiers - Une expérience confirmée du dépassement des objectifs de chiffre d'affaires dans les services financiers, grâce à une gestion efficace d'un pipeline et d'un processus de vente en constante évolution - D'excellentes compétences en communication et l'aisance nécessaire pour présenter devant des publics financiers variés, des analystes et des équipes de recherche jusqu'aux membres de la direction - Une connaissance approfondie des cycles d'achat, des processus de décision et des principales problématiques du secteur des services financiers - Une approche stratégique et analytique du marché des services financiers, alliée à une exécution tactique et créative pour saisir les opportunités - Un intérêt marqué pour les systèmes d'IA avancés et leurs applications dans les services financiers, voire une expérience dans ce domaine. Le développement sûr et éthique des systèmes d'IA de pointe pour les usages financiers vous tient particulièrement à cœur. Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role This is a chance to build the frontier LLM evals that shape the next generations of flagship models. Could a model design a computer chip, or find the backdoor an attacker left in a network? Public benchmarks can't tell us, as they're generally not a good measure of real work. As an Evaluation Engineer, you'll own evals from start to finish. You'll run workshops with customers, industry experts and our customer-facing teams to understand their most important industry use cases (e.g., an engineer updating a part in CAD software), and help decide which are worth building first. You'll also look beyond today's use cases and design moonshot evals for work no model can do yet, so Mistral gets there first. Then you'll turn each one into a benchmark, often one where an agent has to do the work inside real software. You'll source the data, decide how to score it, and run it on every new Mistral model and on competitor models. When our models fall short, you'll work with the post-training teams to close the gap. When they catch up, you'll make the eval harder. You'll write up and present your results so senior leaders can act on them. They also give our go-to-market teams evidence of where Mistral leads. You'll learn new fields quickly. One month you might be learning how chip designers check their work, and the next how a bank investigates a flagged payment. The team is new and fast-paced, and you'll have a lot of autonomy. You'll spend a lot of time speaking with people across Mistral to work out what matters most, then decide what to build. What You Will Do - Run discovery with customers, industry experts and teams across Mistral, then help decide which use cases are worth building first. - Design new benchmarks for industry use cases and frontier capabilities, including how they're scored. - Build evals where agents work inside real software (e.g., CAD and simulation tools), and run them on our models with checks that the results stay reliable over time. - Stress-test existing evals to find flaws and bugs before we rely on them. - Source data with expert vendors. Where customer data can't leave the customer, build realistic proxy or synthetic data instead. - Write up and present what you find so leaders across Mistral can act on it. - Help other teams build their own evals, with tools and guides they can reuse. What We're Looking For Experience - 2+ years of industry experience (e.g., in software, AI, or consulting), or a PhD. - A software engineering or research background, with experience writing code that others can build on. - Experience working directly with customers, industry experts, or other teams (e.g., through consulting, solutions engineering, or research collaborations). - Experience building something with LLMs. - Comfort working with large datasets, including building and cleaning them. Technical - Strong Python skills. - Comfortable working in a large, shared codebase and getting your code through reviews by other teams. - A strong understanding of LLM training, inference, and evaluation. Communication - You enjoy speaking with people and are good at it. - You write clearly. A short doc or deck from you is enough for a busy leader to make a decision. - Confident presenting to both technical and non-technical audiences. - Fluent in English. How you work - High energy, and you don't need a roadmap. You move independently and handle uncertainty with confidence. - Proactive and high-agency. You spot what needs doing and get it done. - You make good decisions about what to build first and can explain why. - Low-ego, collaborative, and eager to learn. - Curious, with a track record of learning things outside your work or studies. You can get to grips with a new field in a few weeks. NICE TO HAVE - Experience building AI evaluations, especially for industry applications. - Published research on evals or contributions to open-source evaluation frameworks. - Experience building datasets, generating synthetic data, developing labelling guidelines, or working with annotation vendors. - A background in an industry outside software (e.g., engineering, finance, or science). What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The mission You will be the reference point for the most complex hardware interventions across our sites. Mistral's compute is our largest investment and the foundation of frontier AI in Europe. As a Senior Data Center Hardware Engineer , you own the interventions that require the highest level of technical expertise: multi-node failures in production, full-rack deployments of GPU-dense systems, and vendor escalations where you speak as the technical authority for our sites. You'll work end-to-end — compute, storage, interconnect, power and cooling interfaces — across our data center footprint, raising the bar on reliability as our capacity grows. This is a hands-on senior IC role: deep technical leadership and mentorship, no direct line management. Location: Based at one of our data centers in the Paris region, with occasional visits to our other sites as needed. What you'll do - Lead complex interventions — vendor-level and multi-node operations in production: full rack builds and bring-up, GPU-dense platform deployment (H100/H200-class and next-gen, including liquid-cooled racks), intricate recabling, post-restart diagnosis. You own the plan, the risk assessment, and the rollback. - Own vendor management — coordinate repairs, part replacements and escalations directly with hardware vendors; hold them to their SLAs; drive proactive fixes from failure trends. - Diagnose at depth — correlate symptoms across compute, storage, interconnect and cooling; read BMC/IPMI consoles, OS logs and crash dumps; methodical root-cause analysis that ends in concrete corrective actions. - Deploy and validate — structured bring-up and validation of new racks and platforms; work with networking and infrastructure teams to take installations from delivery to production-ready. - Lift the team — mentor and pair with L1–L3 engineers on live operations; turn your knowledge into SOPs, checklists and training material; propose and build small automation (Python/Bash) to shorten MTTR. - Work the facility interface — partner with critical facilities/engineering ops on power, cooling (air and liquid), PDU and monitoring (BMS/EPMS) boundaries; enforce ESD/LOTO/PPE and audit-ready change discipline everywhere. - Own spares & reliability — plan spares strategy, track fleet failure trends, and run proactive vendor actions before incidents happen. About you - 6+ years in data center / server hardware or L2/L3 hardware support, including complex hands-on work in production environments (HPC/AI/cloud at scale strongly preferred). - End-to-end hardware expertise: CPU/memory/PCIe (incl. accelerators), NICs, PSUs, drives, network, power and cooling interfaces (DLC included); strong judgment on when and how to escalate. - Diagnostics depth: confident with BMC/IPMI logs, Linux logs and CLI checks; structured root-cause analysis. - Deployment experience: you've taken racks from delivery to production, with concrete examples to show for it. - Vendor fluency: you've managed hardware vendors — RMAs, field replacements, escalations — to concrete outcomes. - Impeccable safety and discipline: ESD/LOTO/PPE without exception; clean, labeled, auditable work. - Communication & mentoring: clear status updates and handovers; able to coach engineers during live incidents with composure. - Mobility: willing to visit our other sites in the Paris region as needed. Nice to have - GPU-dense platform experience: NVIDIA H-series (H100/H200) or GB-series rack deployments. - High-speed interconnects (InfiniBand/RoCE), RAID/storage (NVMe/SAS/SATA), vendor tooling (iDRAC/iLO/IPMI). - Automation (Python/Bash) for ops tooling and reporting; ticketing (Jira/ServiceNow), inventory/RMA flows. - Hardware qualification, burn-in or factory validation background. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role Owns Mistral’s strategic relationship with EY across APAC. Manages the EY relationship and joint go-to-market end to end, delivering revenue and industry impact. Orchestrates multi-country pursuits spanning ASEAN (Malaysia, Thailand, Vietnam, Indonesia and the Philippines), Australia, India, Japan and Korea, owning the seating model, deal economics and partner governance through MD sign-off. Owns partner-leadership access at the change-maker level: AI practice leads, industry MDs and CTOs at regional and global level, including EY Consulting leadership. Architects and operationalises the APAC GSI Partner Playbook: the frameworks, co-sell motions, solution accelerators and delivery-readiness programmes needed to scale frontier AI regionally, including the sovereign AI narrative that differentiates Mistral in regulated markets. Location: Based in Singapore, with travel to ASEAN and APAC countries. What success looks like First 12 months - Executive relationships built across EY Consulting at AI practice lead, industry MD and CTO level, including EY’s Singapore hub and its practices across ASEAN and APAC countries. - A joint EY–Mistral GTM plan live: shared ICPs, vertical use cases, field plays and demand generation, with named account coverage across ASEAN and APAC countries. - One to two named, in-flight APAC deals of flagship scope and complexity, converted from or created through global agreements. - Partner-led and partner-attached pipeline delivered against the team target across sovereign AI, AI Studio and enterprise deployments. - Two to three multi-year GTM agreements or MOUs signed, covering revenue targets, co-sell motions, enablement and commercial frameworks. Key outcomes - Partner-influenced revenue from EY contributes a fifth or more of APAC annual bookings. - Mistral embedded in partner platforms, marketplaces, sovereign-cloud offerings and regional AI Lab programmes. - Certified EY delivery pods operational, with a stable base of partners delivering repeatable demand. Key responsibilities - Own the EY relationship and joint GTM across APAC: executive sponsorship, joint account planning, pursuit support and governance. - Own APAC GSI partner strategy, with EY as the anchor integrator. - Drive EY engagement across ASEAN and APAC countries from Singapore. - Convert or create global agreements and MPAs into named APAC deals; orchestrate multi-country pursuits across ASEAN and APAC countries. - Architect joint GTM: messaging, ICP alignment, vertical use-case strategy, field plays and demand generation. - Guide EY in building profitable Mistral service lines and certified delivery pods. - Lead deal orchestration: partner qualification, commercial alignment, seating model, deal economics and delivery planning. - Own partner scorecards, QBRs, pipeline reviews and performance analytics; ensure MPA, reseller/OEM and AI Lab frameworks are fit for multi-country use. Must have - 8–12+ years driving partner-led revenue with GSIs, hyperscalers, telcos or OEMs across APAC. - Has worked at EY, or has directly managed the EY relationship (alliance, partnership or account leadership), with first-hand knowledge of how EY Consulting operates, including its service lines, practice and industry structure, alliance model, decision-making, and how deals are sold, staffed and governed. - Demonstrated ability to manage a strategic GSI relationship and its joint GTM, operating at AI practice lead, industry MD and CTO level and converting or creating global agreements into named APAC deals. - Track record engaging C-suite and securing multi-year commercial frameworks. - Experience structuring multi-country pursuits, seating models and partner governance requiring MD-level sign-off, including across ASEAN and APAC countries. - Commercial acumen in AI/cloud: able to translate AI Studio, sovereign AI and GPUaaS into clear revenue models. Nice to have - Familiarity with model deployment, GPU infrastructure or AI Lab concepts. - Existing relationships within EY AI/Cloud practices. - Prior use of hyperscaler funding (ECIF, MACC, OCP), MDF or co-sell pipelines. - Exposure to sovereign AI or public-sector transformation in regulated APAC markets, including ASEAN. Ideal backgrounds Current or former EY Consulting leaders (alliance directors, AI/data practice leads, industry or sector leads), and leaders who have directly managed the EY relationship from a vendor, hyperscaler or technology partner side (e.g. senior partner sales managers at AWS, Microsoft or Google Cloud; partner account managers at Nvidia, Dell or HPE); regional or global alliance directors at Deloitte; GTM and strategic partnership leads at fast-growing AI, data or infrastructure vendors. Languages: English required. Mandarin, Japanese or Korean a bonus for multi-country engagement. Bahasa (Indonesia/Malaysia), Thai, Vietnamese or Filipino a plus for ASEAN engagement. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Enterprise Account Executive at Anthropic, you’ll drive adoption of safe, frontier AI by securing strategic deals with top enterprises, unlocking new value streams throughout their business. You’ll leverage your consultative sales expertise to propel revenue growth while becoming a trusted partner to customers, helping them embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM, product, 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 new market segments, pinpointing high-potential opportunities, and executing strategies to capture them. By driving deployment of Anthropic's emerging products, you will help enterprises obtain new capabilities while also advancing the ethical development of AI. Responsibilities: - Win new business and drive revenue for Anthropic. Find your way to the right people at prospective customers, educate them about LLMs, and help them succeed with Anthropic. You’ll own the full sales cycle, from first outbound to launch - Design and execute innovative sales strategies to meet and exceed revenue quotas. Analyze market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities, partnerships, and campaigns - Spearhead market expansion by pinpointing new customer segments and use cases. Collaborate cross-functionally to differentiate our offerings and sustain a competitive edge - Inform product roadmaps and features by gathering customer feedback and conveying market needs. Provide insights that strengthen our value proposition and enhance the customer experience - Continuously refine the sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency You may be a good fit if you have: - 5+ years of enterprise sales experience driving adoption of emerging technologies with a consultative, solutions-oriented sales approach - A track record of managing complex sales cycles and securing strategic deals by understanding multifaceted technical requirements and crafting tailored solutions - Demonstrated ability to navigate dynamic stakeholder ecosystems, building consensus and providing innovative solutions to disparate groups - Extensive experience negotiating highly complex, customized commercial agreements with multiple stakeholders - Proven experience exceeding revenue targets in fast-paced organizations by effectively managing an evolving pipeline and sales process - Excellent communication skills and the ability to present confidently and build connections across all customer levels, from ICs to C-level executives - A knack for bringing order to chaos and an enthusiastic “roll up your sleeves'' mentality. You are a true team player - A strategic, analytical approach to assessing markets combined with creative, tactical execution to capture opportunities - A passion for and/or experience with advanced AI systems. You feel strongly about ensuring frontier AI systems are developed safely 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: £195,000 - £280,000 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.

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE TEAM Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all. We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write. European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on. THE ROLE You will build storage on our cloud. Block, filesystem, and object storage for training runs, sandboxed workloads, and general compute: you help decide what we build, what we buy, and how it adds up to storage our customers can bet a business on. Some layers we deploy and harden from best-in-class vendors. The ones that matter most we write ourselves in Go — S3-compatible object storage, tiering, backup and recovery, caching layers that put cold data on cheap spinning disks. Storage is a strategic bet for this org: the systems you build will define how a gigawatt of European compute stores its data. WHAT YOU WILL DO - Build the storage stack — block, file, object — for training, sandbox, and general compute workloads. - Design and write our own services in Go: S3-compatible APIs, tiering, backup and recovery, caching layers. - Own the data plane: allocation, duplication, tiering, backup and recovery. - Plan capacity across datacenters and across failure domains — petabytes, not terabytes. - Partner with Product Managers to shape the storage roadmap and make the technical and business tradeoffs. WHAT WE'RE LOOKING FOR - You have built storage systems — object, block, or distributed filesystems — not just operated them. You know what happens when a disk dies mid-write and when a rebalance collides with a backup window. - Deep distributed-systems fundamentals: durability, consistency, replication, erasure coding, failure domains. - You have shipped production systems in Go. Systems engineers coming from C++ or Rust who are ready to write Go daily should still talk to us. - You are comfortable with hardware reality: HDD, SSD, and NVMe tiers, and the economics of each. - 5+ years building backend or infrastructure systems. - You have partnered with product, design, and business teams to ship software that reached real users. - A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. What you will do As an AI Deployment Strategist, AI4Eng for Physics and Engineering in APAC, you are Mistral's forward-deployed operator on strategic enterprise accounts across automotive, aerospace, semiconductors, industrial equipment, and energy. You own the delivery of AI solutions for physics and engineering challenges end-to-end. Discovery, Scoping & Solution Design: - Run technical discovery sessions to understand business and engineering requirements. - Identify, qualify, and prioritize use cases aligned with the customer's strategic R&D and product-development challenges. - Translate business goals into a concrete AI roadmap and high-level solution architecture, validating feasibility with Product and Applied AI teams. - Build ROI models and business value propositions, and own scoping documents and SOW inputs. Delivery & Program Management - Own end-to-end delivery: discovery → design → build → deploy → adoption. - Set up the account operating model: governance, decision forums, and cadence. - Drive day-to-day execution: priorities, milestones, unblockers, and risk management. - Drive scope control and change management, ensuring the right artifacts are produced (design doc, runbook, eval plan, rollout plan, handover). - Bring knowledge of processes and regulations from the industries we serve (aerospace, semiconductor, automotive, industrial equipment, energy). Adoption, Value Realization & Expansion - Lead user testing, training, change management, and developer enablement. - Track value realization against agreed KPIs and report to executive sponsors. - Capture field learnings and feed product gaps and platform needs back to Product, Science, and Engineering. About you - Advanced university degree in physics or engineering, or IT. - 5+ years of experience as a (technical) project manager in a relevant industry, e.g., automotive, semiconductors, or aerospace. - Experience in software development, machine learning, and ideally in numerical simulations for physics and engineering (CAE, CFD, FEM, DEM, etc.). - Hands-on coding proficiency (Python at minimum), with the ability to read design docs and hold your own in deep technical conversations with data scientists, ML engineers, and simulation engineers. - Strong grasp of where AI creates value in computational science: surrogate models, PDE solvers, FEM/CFD acceleration, inverse problems, and differentiable simulation. - Familiarity with deployment patterns (SaaS, VPC, on-prem, hybrid), security and compliance basics, and ideally agile project management methodologies. - Strong communication skills with the ability to explain complex technical concepts in simple terms and to manage C-level stakeholders. We are looking for adaptable team players who excel in a fast-paced environment, are ready to own delivery across APAC accounts, and are prepared to support pre-sales motions to contribute to our shared goals and growth. Interview Process - Talent Acquisition screening call (30 min) - 30 min Hiring Manager Interview - 45 min Technical Interview (physics, simulation, and AI deep dive) - 45 min Business Acumen Interview - Panel (Customer Meeting Role-Play & Use Case Scoping Exercise, 1h) - 30 min Value Talk - Reference check What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. The Role We're looking for motivated and tech-savvy Sales Development Representatives (SDRs) with a strong interest in AI to join our growing sales team. In this role, you’ll play a key part in building a healthy pipeline for our Account Executives by qualifying inbound leads and proactively prospecting into high-value target accounts. This is an opportunity to be at the frontlines of a fast-moving AI company, engaging in thoughtful, technical conversations with a knowledgeable customer base. The ideal candidate is results driven, exhibits strong intellectual curiosity of the evolving AI space, and can operate in a fast-paced, highly-dynamic start up environment. You should be comfortable initiating outreach, handling nuanced product discussions, and helping prospects understand the impact of generative AI on their business. Key Responsibilities - Strategically prospect into key accounts across email, calling and Linkedin, communicating Fireworks AI’s unique value proposition - Consistently meet new business opportunity and pipeline generation targets - Craft personalized, tailored outreach through various research methods to prioritize the right accounts and prospects - Qualify and engage inbound leads, ensuring a smooth transition to our Account Executive team - Act as a brand ambassador, educating prospects on the power and potential of our inference solutions - Collaborate with Sales and Marketing to refine messaging and outreach strategies based on market feedback - Stay current on AI/ML trends to conduct informed, relevant conversations with technical and business audiences Minimum Qualifications - Bachelor’s degree or equivalent practical experience - Demonstrated interest in technology sales, with a strong interest AI and machine learning - Excellent communication and interpersonal skills; able to engage confidently with technical stakeholders - Self-motivated and organized, with the ability to manage multiple priorities in a fast-paced environment Preferred Qualifications - Previous startup or entrepreneurial experience, with a proactive and adaptable mindset - Prior experience in a customer facing role, ideally in SaaS, AI, or emerging tech - Familiarity with CRM systems and sales engagement tools (e.g., Salesforce, Outreach, Apollo, etc.) - Degree in engineering, computer science, or a related technical field - Active interest in AI/tech communities with a demonstrated commitment to continuous learning in the space Fireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in the San Francisco/New York City Area for this role is $85,000 - $100,000 per year. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. About the Role We're looking for a hands-on People Operations Specialist to join our People team and keep our day-to-day people operations running smoothly. You'll work side by side with the broader HR team — HRBP, People Ops, Recruiting, and Immigration — to make sure the many moving pieces of a fast-growing company land cleanly: new hires onboard without a hitch, our systems and data stay accurate, and employees get quick, clear answers when they have questions. This role is ideal for someone early in their HR career who wants breadth. You'll touch HRIS, onboarding, contractor operations, immigration support, internal documentation, and employee recognition — and you'll get real ownership in each area. We're looking for someone who's highly organized, comfortable shifting priorities, and able to unblock themselves and keep things moving without waiting to be told how. What You'll Do HRIS & Data Integrity - Own day-to-day updates in our HRIS — start date changes, title and job detail adjustments, reporting line changes, and other employee record maintenance. - Run regular internal data audits to catch and correct discrepancies before they become downstream problems for payroll, benefits, or reporting. - Partner with People Ops, Finance, and IT to keep employee data consistent across systems. Onboarding Logistics - Coordinate end-to-end onboarding logistics for new hires so their first day is seamless, including: - Monitoring background check status and following up on anything pending or flagged. - Completing I-9 verifications and driving follow-ups to ensure timely, compliant completion. - Coordinating with IT on laptop provisioning, email and account setup, and name or address changes. - Managing seat assignments and workspace readiness in partnership with Workplace. - Ordering and preparing new hire swag and welcome materials. - Help facilitate our weekly new hire onboarding sessions — prepping materials, managing logistics and the calendar, presenting portions of the agenda, and gathering feedback to improve the experience over time. - Serve as a friendly first point of contact for new hires, answering pre-start and first-week questions. Contractor Lifecycle Management - Own the contractor lifecycle end to end: onboarding (agreements, signatures, background check bypass proof), contract timeline tracking (start and end dates, early expiration flags, extensions and conversions with managers and Finance), and offboarding (access and equipment return with IT, final documentation). - Keep contractor records, status, and dates accurate at every stage. Immigration Support - Support immigration case processing in partnership with our People team and outside counsel — gathering documents, tracking case status, and keeping timelines on track. - Handle basic immigration questions from employees, candidates, and the recruiting team, escalating complex matters appropriately. - Maintain accurate immigration records and calendar key deadlines and expirations. Internal Documentation - Own our internal HR wiki — keeping pages current, accurate, and easy to navigate as policies and processes evolve. - Document new and changed processes so the team has a reliable single source of truth. Employee Recognition - Support administration of our recognition program, including managing award winner prizes, swag, and fulfillment logistics. - Help keep the program visible and running on a consistent cadence. What We're Looking For - Degree in Human Resources or a related field, plus 2-3 years of experience in an HR Generalist or HR Specialist role. - Highly organized, with a track record of juggling a wide span of workstreams and keeping details from slipping through the cracks. - Resourceful and self-directed — comfortable figuring out a solution when there's no playbook, and able to unblock yourself to get things done. - Comfortable pivoting as priorities shift, and able to re-prioritize quickly without losing track of what's still open. - Strong written and verbal communication skills, with sound judgment about what to handle directly and when to escalate. - Discretion and good judgment in handling confidential employee information. Nice to Have - Experience supporting immigration cases (H-1B, TN, O-1, green card processing, or similar). - Experience in a startup or other high-growth, fast-paced environment. - Hands-on experience with an HRIS such as Rippling - Enthusiastic, positive, and brings great energy — someone people are genuinely glad to work with. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About the job Mistral builds AI systems that enterprises run on their own terms, in finance, manufacturing, defense, healthcare, and the public sector. The Solution organization turns customers' hardest problems into AI they own, run, and scale on Mistral. It is one of the fastest-growing functions in the company: 650 people by end of 2026, across EMEA, the US, and Asia-Pacific, delivering measurable business outcomes for enterprise customers worldwide. The Solution organization includes Deployment Strategists, Applied AI Engineers, Infrastructure Solution Architects, and Applied Scientists. They work with enterprise customers from pre-sales through implementation and deliver AI systems that produce measurable business outcomes. Solution Operations is the function that makes this scale. It runs staffing and capacity planning across regions, the go-to-market motion by industry vertical and capability, delivery processes and tooling, the data behind our decisions, and value and customer-success measurement, with hubs in Europe, North America, and Asia-Pacific. We are hiring a Head of Solution Operations . We are looking for an entrepreneurial COO or a former Forward Deployed Engineer with years of experience. This is a build-the-1-to-10 role: you will take a young, fast-growing function and turn it into the operating system that lets Solution scale from hundreds to thousands of people without losing what makes it work. You will lead a team of program leads and regional operators across three continents, and work as a business partner to Solutions leadership. What you will do - Own the Solution operating system end to end. One process from pre-sales to post-sales, a single source of truth for people, projects, and opportunities, the Solution tooling stack, and safety, security, and compliance built into how the team works. - Industrialize what already works. Turn delivery and vertical playbooks, staffing frameworks, and the value and ROI methodology into reusable assets the whole team runs on, and drive their adoption in every geography. - Build the global operating model. Keep core operations centralized while ensuring real adoption and the right local adaptation across EMEA, the US, and Asia-Pacific, with full-stack regional operators on the ground. - Staff demanding customer engagements. Own capacity planning and forecasting, skills-to-project matching, time-to-staff, utilization, and bench health across all geographies. - Make customer success measurable. Stand up delivery-outcome measurement and customer-satisfaction systems, and run the feedback loop that turns field learnings into product requirements and reusable IP. - Make AI-native operations the default. Build internal tools, agents, and automations that remove manual work from planning, staffing, reporting, and delivery follow-ups, starting with your own team. - Lead and grow the team. Hire, mentor, and develop program leads and regional operators, raise the technical bar of the function, and build the hiring plan for its next phase. - Partner across functions. Work daily with Solution leadership, regional Sales leadership, Product and Engineering, RevOps, and Talent Acquisition, and bring executive judgment on where to invest, slow down, or say no. How We Work in Solution - We care about people and outputs. What matters is what you ship. - The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not copying what worked before. - We say what we mean. Feedback is direct and given because we care. No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it. About you Whatever your path, you bring: - Extensive leadership experience , with demonstrated impact building and leading teams or functions in a fast-scaling environment. - A track record of industrializing something handcrafted but working : processes, systems, and teams that scaled an order of magnitude without losing what made them work. - The ability to bring structure to ambiguity and drive complex, cross-functional initiatives from strategy through execution. You are hands-on and biased toward action. - Data-driven and AI-fluent : you build the internal tools, automations, dashboards, and AI workflows you rely on. - Global operating range : you work naturally across geographies and cultures, with the executive presence to hold a room with C-level stakeholders and the credibility to challenge senior leaders. - Stakeholder management : you align competing priorities and drive decisions without formal authority. - Fluent in English ; additional languages are a plus. Ideally - Experience in enterprise software, AI, or deep-tech delivery, or top-tier strategy consulting on complex technical transformations. - Experience operating at global scale across EMEA, the US, and Asia-Pacific. - Hands-on experience building AI-native operations: automating workflows with LLMs and agents rather than prompting a chatbot. - MBA or advanced degree preferred. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

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

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About the job Mistral AI is looking for a Domain Expert in crashworthiness simulations to help build AI-accelerated simulation capabilities for industrial engineering. You will work at the intersection of industrial simulation, physics modeling, machine learning, and engineering workflows. Your role is to bring deep solid-mechanics expertise into the design, training, evaluation, and deployment of AI Physics Models for real engineering use cases. This is a hands-on technical role. We are looking for someone who understands industrial structural simulation not only conceptually, but through direct experience with simulation models, solver workflows, data generation, validation, and engineering decision-making. You will work with research, product, and customer-facing teams to ensure that our models are useful against real engineering standards — not only benchmark metrics. Relevant application areas may include automotive crashworthiness, aerospace structures, consumer-electronics drop/reliability, manufacturing, durability/fatigue, and other nonlinear structural mechanics problems. What you will do - Work with our research team to define, generate, and iteratively improve simulation datasets for training and evaluating crashworthiness foundation models, balancing coverage of relevant physical scenarios, simulation fidelity, and computational cost. - Design and run high-fidelity simulation campaigns using structural mechanics solvers such as Abaqus, LS-DYNA, Ansys Mechanical, Radioss or equivalent tools. - Define the relevant variation space for training data: geometry, mesh resolution, material behavior, boundary conditions, loading, contact, joints, failure modes, and engineering KPIs. - Build or guide automated pipelines for simulation setup, execution, post-processing, dataset creation, and model evaluation. - Work with research teams to train and evaluate AI models on simulation data, and diagnose failure modes caused by data gaps, poor coverage, numerical artifacts, or model limitations. - Evaluate model outputs against industrial engineering needs, including field-level accuracy, scalar KPIs, deformation modes, load paths, energy absorption, stress/strain fields, failure indicators, uncertainty, and out-of-domain behavior. - Work with industrial customers to understand their simulation workflows and engineering priorities, define use cases and success criteria, and incorporate their feedback into model development and validation. About you - You have deep expertise in crashworthiness, solid mechanics, and structural mechanics, with substantial experience in industrial simulation workflows. - You have a Master’s degree or equivalent technical depth in mechanical engineering, aerospace engineering, civil/structural engineering, computational mechanics, applied physics, or a related field. - You have 4+ years of relevant industrial experience (or PhD +1 years) in domains such as automotive, aerospace, and consumer electronics. - You have hands-on experience with explicit dynamics for crash or impact simulation and understand nonlinear FEM and related topics such as contact, plasticity, structural dynamics, buckling, material modeling, fracture/damage, fatigue, crashworthiness, or durability. - You have direct experience with simulation validation, correlation, model quality, numerical sensitivity, and engineering KPI definition. - You are a strong Python developer who can build and maintain reliable tools for simulation automation, data processing, and model evaluation. You apply sound software engineering practices, including version control with Git, automated testing, code review, and clear documentation. - You have hands-on experience working in Linux and HPC environments, including submitting and monitoring batch jobs, selecting appropriate compute resources, and troubleshooting simulation workflows. You can run simulation campaigns efficiently across a compute cluster. - You are comfortable operating in ambiguous technical environments and turning poorly defined industrial problems into scoped datasets, experiments, metrics, and execution plans. - You communicate clearly with both deep technical experts and non-specialist stakeholders. It would be great if you - Have experience applying machine learning, surrogate modeling, reduced-order modeling, optimization, or data-driven methods to simulation problems. - Have contributed to reusable internal tools, open-source code, simulation automation frameworks, or production-quality engineering workflows. - Have experience working directly with industrial customers, product teams, or engineering decision-makers. - Have publications, patents, internal technical leadership, or recognized contributions in engineering, simulation, computational mechanics, or ML-for-physics communities. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

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 building the Forward Deployed Engineering team to help the world's most ambitious organizations adopt Claude in ways that are transformative, safe, and lasting. Our Technical Deployment Leads (TDLs) and Forward Deployed Engineers (FDEs) embed with strategic customers to ship production AI applications that solve real business problems. Our delivery model pairs two roles: FDEs own the technical artifact, and TDLs own the engagement end to end, from statement of work (SOW) through production deployment. As a Manager of Technical Deployment in EMEA, you lead a team of TDLs embedded with strategic customers. You own engagement portfolio health across your team, set the bar for delivery quality, and define where we play: which customers and which use cases are ready for production AI today. Your work will directly influence Anthropic's product direction and establish Anthropic as the trusted partner for AI transformation across the region. This role is based in London. This is a player-coach role. You need to be credible in architecture conversations with a customer's engineering leads and equally comfortable in front of executive sponsors. You will also lead the most complex engagements yourself when the stakes call for it. Most of your impact will come through the people you hire and the standard you hold them to. You won't write production code, but you will pressure-test the technical decisions your TDL team makes with FDEs. Responsibilities - Hire, develop, and retain a team of TDLs embedded in engagements across EMEA. Set a high bar for delivery judgment, technical fluency, and customer presence, and run the interview loop that holds that bar. - Manage each TDL directly: regular 1:1s, clear expectations, direct feedback, and a growth plan. Build a bench that runs engagements well without you in the room. - Define the delivery strategy for your portfolio: which kinds of companies we engage, which use cases we prioritize, and how that differs by market and industry. Hold each TDL accountable for a clear account strategy: what we want to achieve with the customer and the exit gates that tell us we got there. - Own portfolio health across your team. Track which engagements are on track, at risk, or closing out, and intervene early when delivery drifts. Run engagement quality reviews with your team. - Own customer outcomes across the portfolio. Hold the executive relationship with customer sponsors, run steering committees, and represent Anthropic with senior business, risk, legal, and engineering leaders. - Make the staffing call for each engagement. Work with FDE managers to match TDLs and engineers to each customer, and adjust as scope changes. - Lead the most complex engagements yourself. Take the TDL seat when engagement size, regulatory exposure, or organizational complexity calls for it, from SOW through production deployment. - Set the bar for delivery excellence: SOW quality, MVP scoping, and value measurement. Ensure every engagement has a defensible impact story. - Build regulatory requirements into how the team scopes and delivers, working with Legal, Security, and customer risk functions, so compliance shapes the plan from the start rather than blocking it late. - Codify reusable solution patterns, evaluation frameworks, and technical playbooks across the team. Turn what works in the field into delivery infrastructure that lets the practice scale, and adapt global playbooks to EMEA markets. - Partner with Sales to qualify engagements, shape scope, and inform SOWs. Partner with Marketing and Sales on EMEA go-to-market materials, reference cases, and positioning. - Run the team's operating rhythm: engagement reviews, knowledge-sharing, and escalation support, and feed the wider post-sales cadence and dashboards. Set team goals tied to customer outcomes. - Bring the field back to Anthropic. Surface delivery lessons and emerging use cases from EMEA to Product and Research, and represent the region in leadership discussions. - Consistently uphold Anthropic's values as you lead your team. TDLs should be strong representatives of Anthropic's culture as they work within customer environments. - Travel to customer sites across EMEA (25–50% expected), with occasional travel to the US. You May Be a Good Fit If You - Have 8+ years leading enterprise AI/ML delivery, whether you came up as a founder, engineer, data scientist, or researcher and moved into deployments, with at least 3 years directly managing people who owned delivery outcomes. - Have a track record of building and leading technical delivery teams in enterprise environments across more than one EMEA market, ideally including embedded or forward-deployed teams working at client sites. - Have delivered AI/ML or LLM-based agentic solutions into production. You understand solution patterns, integration approaches, and what breaks in real environments. - Bring depth in at least one industry (e.g., financial services, healthcare and life sciences). You understand how security, compliance, and regulatory review shape what ships, and you can speak credibly with a CIO, a chief risk officer, and a head of engineering. - Know the EMEA enterprise landscape: how buying and procurement differ across markets, and how regulatory requirements affect what customers can deploy. - Can navigate architecture discussions with engineering stakeholders, evaluate technical trade-offs, and judge whether a proposed agent design is realistic. - Have experience with value-based scoping, including TCO/ROI quantification and post-deployment impact measurement. - Thrive in ambiguity and bring structure where none exists. You have built a team, practice, or function from an early stage. - Have executive presence: polished, credible, and concise with senior leaders in high-stakes settings, and just as effective in a hands-on engagement review with your team. - Have strong written and verbal communication skills. You can translate technical complexity into clear narratives for diverse audiences. Working proficiency in a second European language such as German or French is a plus. 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: £190,000 - £230,000 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.

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About the Role As a Research Engineer, GPU performance , you will sit at the heart of that spectrum: your low-level work directly determines how fast our frontier models can be trained and served. Working hand-in-hand with Research Scientists, you'll make every GPU count. Mistral AI is hiring an expert in pushing large language model's GPU utilization and performance to their limits.. In this role, you will own the performance of our models end-to-end: writing the low-level code that extracts the maximum capacity from high-end hardware, and rethinking model architectures so they run efficiently at scale. What You Will Do - Develop low-level code that takes full advantage of high-end GPUs and maxes out their capacity — from custom kernels to memory-layout and communication optimisations. - Rethink parts of the generative model architecture to make them more suitable for efficient inference, in collaboration with Research Scientists. - Integrate low-level efficient code into a high-level MLOps framework , so that optimisations benefit every training run and deployment rather than a single experiment. - Profile, benchmark and squeeze performance out of large-scale training and inference on thousands of GPUs. - Model LLM execution on various GPUs with high fidelity to assess hardware usage and build serving performance estimates. What We're Looking For - High technical competence for writing custom low-level kernels and pushing GPUs to their limits. - High expertise in the distributed computation infrastructure of current-generation GPU clusters. - Overall understanding of the field of generative AI ; knowledge of, or interest in, fine-tuning and using language models for applications. - Strong software-design instincts: testing, code review, CI/CD. - Self-starter, low-ego, collaborative. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI Engineer on the Startups team at Anthropic, you will be a trusted technical advisor to the top AI-native startups building in the physical world, across robotics, semiconductors, aerospace, manufacturing, and civil infrastructure, as they grow from early product to scale. Some of these companies build the hardware itself and want Claude woven into how they design, test, and operate it, and others build the software that engineers everywhere use to design, simulate, test, and scale, and this role works with both. You'll lead deep technical engagements, partnering directly with startup software and hardware engineering teams to help them build their products on Claude and run their own engineering with it, advising on implementation and agent design as they build what is newly possible with AI in the physical world. You will bridge the gap between what Claude can do and what it takes to build real things, working alongside some of the strongest teams in the field on problems that matter and helping mechanical, electrical, and process engineers get the kind of step change that software engineering has had from agentic coding with tools like Claude Code. Working closely with Applied AI Architects, Account Executives, and Anthropic's Product, Engineering, and Research teams, you'll help startups build at the edge of what is possible with Claude. You'll leverage your AI engineering expertise and your engineering domain knowledge to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable physical AI startups to succeed with Claude. Responsibilities - Serve as a deep technical advisor to high-potential startups building in the physical world, whether Claude sits inside the product they sell or inside the way they design, test, and run their own hardware, working alongside them to push the boundaries of AI in engineering, manufacturing, operations, and more - Work hands-on with startup software and hardware teams through pair programming and architecture reviews that accelerate their development, and understand their engineering workflows end to end, from design and simulation through test, production, and operations, so that your guidance fits how real hardware gets built - Develop prototypes and technical documentation, including evaluation suites, benchmarks grounded in real engineering tasks, AI engineering techniques, and architecture diagrams, that enable startups to build, operate, and scale with Claude - Create reference implementations and sample code that many companies can adopt without starting from scratch, for example integrating Claude with CAD, simulation, design tools, or industrial automation - Collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements - Identify patterns across engagements, including what is hard about applying AI to physical systems such as reading drawings, 3D geometry, board layout and routing, GD&T, latency and on-premise constraints, and physical safety, then build repeatable evaluations and solutions and contribute insights back to Product, Engineering, Research, and the broader Applied AI team - Create technical content for startup audiences including documentation, tutorials, and sample code - Foster community engagement through hackathons, webinars, technical office hours, and startup-focused events - Travel to customer sites for workshops, implementation guidance, and relationship building You may be a good fit if you have - Deep engineering experience in a physical discipline such as mechanical, electrical, aerospace, robotics, semiconductor, manufacturing, or civil engineering, gained by designing, building, or operating real hardware, along with strong opinions of your own about how to bridge the gap between what AI can do today and how physical things get built - 4+ years of technical experience as a software engineer, ML or research engineer, robotics or controls engineer, hardware or systems engineer, or technical founder, with either production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale, or a track record of successfully applying AI to real engineering work in design, simulation, test, or production - Experience with startups or high-growth companies and a love of working with founders and small teams that move quickly - Strong technical communication skills, with the ability to translate complex AI concepts into architectural decisions and actionable implementation plans for both software and hardware engineering audiences and to run technical workshops, hackathons, or developer-focused events - A collaborative approach to working across teams, the range of a generalist who can context-switch from robots to chips to rockets to factories and get up to speed on a new domain quickly, and a passion for making powerful technology safe and beneficial 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 - $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.

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. About the Role Fireworks AI is looking for an experienced General Ledger Accountant to own and scale the company's month-end close and general ledger as the business grows rapidly. This role will be responsible for the journal entries, reconciliations, and supporting schedules behind our operating expense accounts and international subsidiaries (APAC and EMEA), including high-volume areas like infrastructure and compute spend, software subscriptions, and prepaid commitments, while helping build the processes, documentation, and controls needed to support a high-growth AI infrastructure business. This person will partner closely with Accounts Payable, Payroll, FP&A, Tax, Legal, and Procurement to ensure transactions are coded, recorded, and reconciled correctly. The ideal candidate is hands-on, detail-oriented, and comfortable owning the close in an environment where systems and processes are still being built. What You'll Do - Prepare and post journal entries for accruals, prepaids, reclasses, and fixed asset depreciation within the close calendar. - Own operating expense accruals, gathering support from Accounts Payable, Procurement, and budget owners and truing up against actuals. - Maintain prepaid schedules and amortization, including software subscriptions, cloud and compute commitments, and usage-based prepaids. - Perform monthly flux and variance analysis on operating expense accounts and explain the drivers, such as headcount, compute, and software spend. - Reconcile balance sheet accounts monthly, including cash, prepaids, accrued liabilities, deposits, fixed assets, and intercompany, and clear reconciling items with Accounts Payable, Payroll, and Treasury. - Tie out payroll and benefits postings to the general ledger. - Support month-end close and reporting for international subsidiaries, including intercompany transactions, eliminations, and FX remeasurement. - Assist with local statutory and tax filing requests for international entities. - Keep general ledger coding accurate across the ERP and spend management platforms, flag mis-mapped transactions, and help maintain the chart of accounts. - Participate in ERP enhancements and upgrade testing, including before-and-after trial balance and GL detail comparisons. - Document close procedures and help build SOX-ready controls, including preparation, review, and evidence standards. - Prepare PBC schedules and supporting workpapers for external auditors and tax advisors, and respond to questions on your accounts. - Identify manual steps in the close and help automate them using ERP functionality and AI-enabled processes. - Assist with tax, compliance, and other accounting projects as needed. What We're Looking For - 4–6 years of general ledger or corporate accounting experience, ideally including time at a high-growth technology or SaaS company; public accounting experience a plus. - Strong grasp of U.S. GAAP and accrual accounting, including prepaid and capitalization policy. - Hands-on experience owning month-end close tasks, including journal entries, accruals, and balance sheet reconciliations. - Experience with multi-entity accounting, intercompany, and foreign currency a plus. - Strong systems orientation, including experience with ERPs such as NetSuite; familiarity with spend management platforms such as Ramp a plus. - Advanced Excel skills and the ability to build clean, auditable schedules. - Experience supporting external audits and preparing clear supporting documentation. - Exposure to SOX readiness, internal controls documentation, or an ERP implementation or chart-of-accounts redesign a plus. - Strong communication skills and comfort asking questions early and partnering across teams. - Comfortable working in an environment with rapidly evolving systems and changing business requirements. - Bachelor's degree in Accounting, Finance, or related field. CPA or progress toward CPA preferred. What Success Looks Like In the first 6–12 months, this person will have: - owned a consistent, on-time close for operating expense accounts and international subsidiaries; - built reliable accrual and prepaid schedules that hold up at audit; - kept balance sheet reconciliations current, with reconciling items cleared each month; - improved GL coding accuracy across the ERP and spend management platforms; - documented close procedures and controls for their accounts; and - reduced manual effort in the close through automation and cleaner processes. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What's Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. - Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role We are seeking an experienced Engineering Leader to build the partnership engineering organization. In this role, you will lead and build a new team dedicated to the technically complex work we do with our Partners, turning that work into repeatable product features. You’ll work to scale the team as they grow, help prioritize and support work in a fast paced environment, and build a healthy team culture. This is a highly visible role with the opportunity to shape how Mistral’s technology is adopted globally and unlock large business opportunities What You Will Do - Remove obstacles and create an environment where your team can focus on building solutions. - Own the most critical partnerships of the company and what's required to make them a success. - Translate product vision into technical reality, collaborating closely with the Product team. - Ensure applications are performant, stable, and responsive. - Uphold high code quality standards through reviews, testing, and automation. - Own the full software development process, from design to deployment. - Plan projects, including roadmaps, deadlines, and task allocation. - Collaborate with stakeholders across Engineering, Product, and Design, and Partners. - Support team growth through hiring, onboarding, and mentorship. What We're Looking For - Experience building and managing engineering teams. - Proficiency in Python and at least one web framework (FastAPI, Django, Flask). - Proficiency in C#, Golang, TypeScript and at least one web framework. - Experience with large-scale distributed systems. - Experience working with cross-functional teams, such as Product, Design, and Business. - Strong problem-solving abilities and attention to detail. - Ownership mindset and ability to ship products end-to-end. - Excellent communication skills and a low-ego, team-first attitude. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. Responsibilities - Push search and agent quality forward through improvements to models, training data, tools, and system design. - Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. - Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. - Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. - Improve retrieval and ranking models and the search interfaces agents use to find and assess information. - Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. - Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. - Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. Qualifications - A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. - Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. - Experience designing rigorous evaluations, diagnosing failures, and translating experimental results into practical improvements. - Comfort with open-ended problems that require both research judgment and hands-on engineering. - A strong sense of ownership, curiosity, and the drive to carry an idea through to a working system. Nice to have - Experience with training models to use tools or complete tasks over many steps. - Multi-agent training, coordination, or evaluation. - Building agent harnesses, distributed training systems, or scalable inference infrastructure. - Large-scale retrieval, ranking, or recommendation systems.

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

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking a Program Manager to join our Accounting organization and help it run as one global team. Accounting is scaling at an unprecedented pace across multiple hubs, and the goals, rhythms, programs, and people that make up the team need to stay connected as we grow. In this role, you will own that connective tissue: the annual goal-setting cycle, the leadership team’s operating cadence, org-wide events and internal communications, and the programs that make a distributed team feel like one. You will partner with Accounting leadership, the People team, Finance Systems, and hub leads. This is a hands-on role with a lot of range: part chief of staff, part program manager, part culture builder. Responsibilities Goals and operating rhythm - Run the annual goal setting process and the reporting that tracks progress against those goals. - Look at how the org actually operates (meetings, handoffs, planning cycles, decision making) and fix what isn't working. - Maintain one org-wide planning calendar that shows close, audit, and team milestones alongside company-wide and team events, so leaders can see the pressure points and plan around them. - Build and maintain a simple set of org health metrics (attrition, engagement scores, hiring pipeline, training completion, survey trends) and report on them regularly. Leadership and org-wide events - Run our extended leadership team (XLT) program, including agendas, meetings, follow-ups, and action items. - Own planning and agenda for the annual offsite and run the quarterly team all-hands. - Write the internal updates: a regular team newsletter, plus talking points when leadership needs to explain a change to the whole org. People and culture - Coordinate projects across the org that support employee experience programs. - Partner with the People team to roll out training and development programs for Accounting. - Review team survey results, identify the themes, and build action plans to address the feedback. Follow through and report back to the team. - Run hub programs, including visit and rotation programs, local hub events, and meeting norms that work across time zones, so we feel like one global team. - Run recognition and team rituals: wins, milestones, anniversaries, and peer recognition, especially across hubs. Team operations - Support contractor management, including onboarding, tracking, and coordination with the right partners. - Keep the team's knowledge base current: wiki, org charts, role descriptions, and key process docs. - Keep the team calendar accurate so everyone knows what's coming. Preferred qualifications - 7+ years in program management, operations, chief of staff, or strategy roles. Experience inside a finance or accounting org is a plus, but not required. - A track record of running recurring programs end to end and getting people to follow through without formal authority. - Good judgment about what matters and what doesn't. You can handle a lot of moving pieces without dropping them. - Clear, direct writing. You can brief a senior leader in a few sentences. - Comfort with confidential information and sensitive people topics. - Experience supporting distributed or global teams. - You're organized, but you also know when a process is getting in the way and should be simplified. 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.

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. What You’ll Do - Own Fireworks AI’s global revenue accounting function, including revenue recognition, contract review, close, reconciliations, reporting, and related controls. - Serve as the company’s technical accounting expert for revenue recognition under ASC 606. - Review complex and non-standard customer contracts and determine the appropriate accounting treatment. - Prepare and maintain technical accounting memos supporting revenue recognition conclusions and significant judgments. - Partner closely with Sales, Legal, Deal Desk, FP&A, Billing, and Finance to evaluate the accounting implications of new products, pricing models, and contract structures. - Establish scalable revenue accounting policies, processes, and controls as the company grows. - Lead monthly and quarterly revenue close activities, including deferred revenue, contract assets and liabilities, variable consideration, and revenue-related balance sheet accounts. - Support external audits and serve as the primary point of contact for revenue-related accounting matters. - Identify opportunities to automate and improve revenue accounting workflows, systems, and data integrity. - Build and lead a high-performing revenue accounting team over time. - Support broader technical accounting initiatives, financial reporting requirements, and readiness for future public-company standards. What We’re Looking For - 10+ years of progressive accounting experience, with substantial experience in technical revenue accounting. - Deep expertise in ASC 606 and experience applying the standard to complex technology or SaaS contracts. - Strong understanding of usage-based, consumption-based, subscription, and enterprise contract structures. - Experience evaluating non-standard terms such as minimum commitments, prepaid credits, discounts, rebates, service-level arrangements, contract modifications, and variable consideration. - Strong technical accounting research and memo-writing skills. - Experience working in a high-growth technology company; experience with AI, cloud infrastructure, developer platforms, SaaS, or consumption-based businesses is especially relevant. - Prior experience managing revenue close processes, internal controls, and external audit relationships. - Ability to partner effectively with commercial teams while maintaining sound accounting judgment and appropriate controls. - Strong systems orientation and experience scaling revenue accounting processes through automation. - CPA strongly preferred. - Public accounting experience, particularly with a Big Four firm, is preferred. What Success Looks Like You will build a technically rigorous and scalable revenue accounting function that enables Fireworks AI to grow quickly while maintaining accurate financial reporting. You will be a trusted advisor on complex deals and new business models, ensuring that revenue accounting considerations are understood early and reflected appropriately in the company’s financial statements. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The team Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all. We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write. European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on and shape the team building it. The Role This is a founding people-leadership role. There is no team to inherit and no legacy to maintain — you build the team as well as the stack, and you are accountable for both from day one. Early on you will be deliberately hands-on, because there is no one else to solve the hardest problems — but hiring your first engineers, coaching them, and setting their growth paths starts immediately, not later. If you are looking for a senior IC role, this is not it. You will be the founding Engineering Team Lead for storage on our cloud. Block, filesystem, and object storage for training runs, sandboxed workloads, and general compute: you decide what we build, what we buy, and how it adds up to storage our customers can bet a business on. Some layers we deploy and harden from best-in-class vendors. The ones that matter most we write ourselves in Go — S3-compatible object storage, tiering, backup and recovery, caching layers that put cold data on cheap spinning disks. As the team grows, the balance shifts toward people leadership, and you decide how fast. You will own capacity planning across datacenters and the architecture that keeps data durable when disks, networks, and entire sites fail. Storage is a strategic bet for this org: the team you build and the calls you make will define how a gigawatt of European compute stores its data. What You Will Do - Stand up the storage stack — block, file, object — for training, sandbox, and general compute workloads. - Make the build-vs-buy calls: deploy and harden vendor platforms where they win; design and write our own services in Go where they don't. - Own the data plane: allocation, duplication, tiering, backup and recovery, S3-compatible APIs. - Plan capacity across datacenters and across failure domains — petabytes, not terabytes. - Build the team from zero: make the first hires, onboard and coach them, own performance and growth paths, and set the standard for ownership. - Partner with Product Managers to shape the storage roadmap and make the technical and business tradeoffs. What We're Looking For - 2+ years of real people leadership. You have managed engineers — hired, coached, given honest feedback, and grown them. Hands-on contribution matters here, but this role is judged on the team you build and lead, not just the code you write. - You have built storage systems — object, block, or distributed filesystems — not just operated them. You know what happens when a disk dies mid-write and when a rebalance collides with a backup window. - Deep distributed-systems fundamentals: durability, consistency, replication, erasure coding, failure domains. - You have shipped production systems in Go. Systems engineers coming from C++ or Rust who are ready to write Go daily should still talk to us. - You are comfortable with hardware reality: HDD, SSD, and NVMe tiers, and the economics of each. - 8+ years building backend or infrastructure systems. - You have partnered with product, design, and business teams to ship software that reached real users. - A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About the Role We are hiring an LLM Scientist to push the boundaries of AI-driven scientific discovery. You will specialize in developing and optimizing large language models (LLMs), agentic AI, and deep learning frameworks to solve open problems in the natural sciences: Biology, Chemistry, Physics, and/or Materials Science. Your work will empower scientists with cutting-edge AI tools and accelerate research through: - Model-centric innovation : Improving LLMs’ capabilities to tackle complex scientific problems (e.g., literature synthesis, autonomous experimentation, rigorous derivations). - Cross-disciplinary collaboration : Partnering with Natural sciences domain experts to translate AI advancements into real-world scientific impact. What you will do - AI/ML Research : Participate in end-to-end training of LLM-based solutions, with a focus on scalability, generalization, and scientific applicability . - Data creation : Design original workflows to accumulate high quality scientific data at scale, either through synthetic or crowd sourced pipelines. - Algorithm Design : Use and improve reinforcement learning, or agentic systems tailored to Natural sciences challenges (e.g., modeling resolution, material property prediction, advanced data analysis and coding). - Interdisciplinary Bridge : Work closely with domain scientists to identify AI opportunities and refine models based on feedback. - Tooling & Infrastructure : Contribute to company infrastructure to improve usability for model training in scientific contexts and open-source AI tools for science for non-AI experts. - Autonomous Innovation : Set a research agenda for AI in science, exploring high-risk/high-reward ideas. What We're Are Looking For - AI/ML Expertise : Strong background in LLMs, deep learning, or agentic AI , with a track record of applying these to real-world problems (publications, open-source contributions, or deployed systems) – at the minimum extensive experience in computer science and ideally experience scaling synthetic data generation. - State-of-the-art Knowledge : Familiarity with the latest advancements in LLM architectures and post training. - Technical Depth : Hands-on experience with PyTorch/TensorFlow/JAX , model optimization, and scaling techniques (e.g., fine-tuning, RLHF). - Scientific Capability : Ability to understand 1 Natural Science domain at a high level (e.g., graduate level specialization + general undergrad knowledge) to design effective AI solutions. - Engineering Rigor : Proficiency in scientific computing (e.g., numerical methods, HPC) and software best practices. - Collaboration : Experience translating technical AI concepts for non-experts (e.g., scientists, engineers) and iterating based on user needs. - Mindset : Low ego, team player, and eager to tackle operational challenges (e.g., data pipelines, model deployment). Motivational paragraph When applying for the AI for Science team at Mistral, please describe in a short paragraph a potential project that you would like to contribute to the team, why it is challenging and interesting in general, and more specifically for Mistral. Please also highlight the specific skill set that you can bring to the team. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. About This Role Developers decide what infrastructure wins. They try three platforms in an afternoon, keep the one that got them to a working inference call fastest, and tell everyone else about it. As a Developer Advocate at Fireworks, you own a piece of that decision: you make Fireworks the platform developers reach for first when they want to build, fine-tune, and serve frontier open models in production. You do that by building things worth showing, not by talking about things other people built. This role has a dual bar, and we mean both halves of it. You are a working engineer: you ship code, read diffs, deploy models, and can hold your own in a conversation about batching, quantization, or why a fine-tune regressed. You are also a public technical communicator: you write clearly enough that a senior engineer forwards it, you're good on a stage, and you have or want a real presence in the places developers actually argue about this stuff. Most people are strong at one and passable at the other. We're looking for the rarer profile who is genuinely credible at both, because in AI infrastructure the audience can tell within one paragraph whether you've actually run the thing. The field moves weekly. A major open-weights model drops and the window to be the definitive resource on it is measured in days. Your job is to be one step ahead of that cadence, consistently, and to make it look repeatable rather than heroic. This is one of the first advocate seats on the team, which means you'll help set the standards: for content, for launch response, and for how we show up. We're hiring at either the Senior or Staff level and will determine level through the interview process based on your experience. Location and Work Style This role is based in San Mateo, CA or London. You'll travel regularly to the conferences, hackathons, meetups, and partner events where the developer community shows up. Expect roughly 20% to 25% travel in a typical quarter, concentrated around major events and launches. If you're based in London, you'll anchor our presence in the European developer community, work across time zones with a primarily US-based team, and travel periodically to our San Mateo HQ for onsites and planning. What You'll Do Build things developers can run. Ship cookbooks, quickstarts, reference applications, and end-to-end tutorials that take a developer from zero to a working inference call and then to something production-shaped. Everything you publish is code someone can fork and run, not a screenshot of code that worked once on your machine. The bar is content a senior engineer respects and a new developer can follow, ideally both in the same artifact. Own the launch response. When a significant model or technique lands, you're among the first credible voices with a working demo, an honest benchmark, and a "how to actually use this today" guide. You'll help build the internal loop (model access, eval harnesses, publishing paths) that makes day-one content a process rather than an all-nighter. Show up where developers are, owned and unowned. On our properties, that's docs, blog, examples, cookbooks, Discord, and the developer newsletter. On properties we don't own, that's GitHub, X, Reddit, YouTube, Hacker News, and the open-source projects our developers depend on, including contributing code and reviewing PRs where it matters. You answer real questions in public and turn the recurring ones into permanent content. Speak, teach, and run the room. Conference talks, hands-on workshops, hackathon mentoring, and developer dinners. You'll help decide where Fireworks shows up and what we say when we get there, and you'll build the material so the next person can deliver it without starting over. Be the developer's voice inside Fireworks. Bring friction, feature gaps, and unmet needs back to product and engineering with evidence: a failing repro, a thread of five people hitting the same wall, a competitor's ergonomics that are simply better. Then close the loop publicly when we ship the fix. Measure what you do. You'll instrument your own work: what content drove signups, which events produced developers who actually built something, where people fall out between first call and production. We care about adoption, activation, and time to first successful build. We do not care about impressions, booth scans, or attendance counts, and we won't ask you to report them. What Success Looks Like in the First Year - You've published a body of technical work (tutorials, apps, deep dives) that developers cite and competitors read. - When a major model drops, Fireworks has authoritative, runnable content out fast enough to be part of the conversation rather than a follow-up to it. - You have a credible, recognized presence in developer communities where we weren't previously part of the discussion. - You've spoken at multiple significant events and left behind a workshop or talk that others on the team can now deliver. - Product and engineering can point to specific roadmap decisions that changed because of feedback you surfaced. - The content and launch standards you set are what new advocates onboard into, and they hold up without you in the room. What We're Looking For - 5+ years of combined engineering and developer-facing experience , with real time in both. For example, several years shipping production software plus meaningful time in DevRel, developer education, technical writing, or solutions engineering. We're flexible on the ratio and inflexible on the requirement that both are genuinely there. - You can code and read diffs. Strong Python; comfortable in TypeScript/JavaScript. You've built and deployed applications yourself, and you can review someone else's sample and tell whether it's good. - Hands-on with the modern AI stack. You've worked with LLM APIs in production, built with at least one agent framework, and have personally fine-tuned, evaluated, and deployed a model, not just read about it. You understand what inference latency, throughput, and cost actually depend on. - A public track record. Technical writing, talks, videos, open-source work, or a following you earned. Something we can go read or watch that shows you can explain hard things well to engineers. - Demonstrated speaking ability. You've presented at conferences, meetups, or workshops, and you're comfortable doing it on short notice about something that shipped last week. - Learning velocity. You can go from "this paper came out Tuesday" to "here's a working implementation and an honest assessment" quickly, and you have a system for staying current rather than relying on luck. - Ownership instinct. You pick your own topics, scope your own projects end to end, and don't need a content calendar handed to you. This role is early enough that you'll be defining the work as often as executing it. Bonus Points - Open-source contributions or maintainership in the AI/ML ecosystem, including inference engines, model libraries, agent frameworks, and evaluation tooling. - Depth in inference optimization, serving architecture, post-training, or evaluation methodology. - You've built something that outlived your direct involvement: a content operation, a launch process, an events playbook, or a community program. - Comfort making video. - Existing relationships with AI research or open-model communities. - You use frontier coding agents in your daily work and have opinions about where they help and where they don't. - Experience being early on a DevRel team and helping establish how it operates. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Account Abuse team is tasked with ensuring Anthropic's computing capacity is allocated fairly, minimizing resources available to bad actors and preventing them from coming back. As a software engineer on this team, you will build the machine learning systems that help us detect and stop abuse at scale. The ideal candidate can see things from opponents' perspectives, understand their means and motives, and anticipate their responses to countermeasures. We're looking for full stack machine learning engineers with experience across model training, productionization, and evaluation. You'll also look for ways to use Claude to speed up how these models get built and maintained. This is classical ML on structured and behavioral data. You do not need a deep learning background or knowledge of LLM internals. What matters is that you have trained and shipped models where the stakes are real, and that you care about building robust production systems as much as the model itself. A false positive here is a legitimate customer locked out, so measurement, precision, and safe rollout are part of the job. Key responsibilities - Build and operate a feature computation platform that serves both model training and real-time scoring, with point-in-time correct training data and low-latency online retrieval - Train, evaluate, and deploy models that detect account-level abuse and fraud, running them both offline and online - Build tooling that automates more of the model development lifecycle, including using Claude to speed up feature development, training, and evaluation - Make backtesting, shadow deployment, and staged rollout the default path to production, with monitoring for training / serving skew, drift, and adversarial adaptation - Work with our data scientists and our Policy & Enforcement team to improve label coverage and quality - Partner with product and platform teams to gather signals and integrate model decisions with minimal impact on their systems' latency, stability, or overall architecture Minimum qualifications - Proficiency in Python and SQL - Experience training machine learning models and deploying them to production - Experience building data pipelines with a batch processing engine (e.g., Spark, Beam) and a workflow scheduler (e.g., Airflow) - Working understanding of point-in-time correctness and training / serving skew, and how to prevent both - Strong communication skills and ability to explain technical tradeoffs to non-technical stakeholders Preferred qualifications - Experience building or operating a feature platform such as Chronon, Feast, or Tecton - Experience with stream processing engines such as Flink, Beam / Dataflow, or Kafka Streams - Experience training ML models in a production setting with demanding serving requirements, such as fraud, risk, or ranking - Experience with tree-based models on tabular data - Experience building unsupervised, clustering-based or graph-based detection systems to surface coordinated account abuse - Experience in integrity, spam, fraud, or abuse detection - Experience working with scarce, delayed, or noisy labels - Experience with AutoML or other approaches to automating the ML workflow - Care about the societal impacts of AI and want your work to make powerful systems safer 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.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most. About the Role We're looking for an Applied AI Engineer to join our Beneficial Deployments, Life Sciences team. Our goal is for Claude to close the loop on scientific discovery, and a significant part of this is helping Claude to drive scientific hardware and software. You'll help deploy the Model Hardware Standard (MHS) to labs doing the world’s most important research. You’ll scale what you learn in the field by contributing back to the standard, building scalable assets, and driving associated internal product and research direction. Responsibilities - Work with labs to automate their experiments end-to-end with Claude - from advising, to prototyping, to writing production code. - Drive product, engineering and research direction based on field experience - e.g. building evals to measure limitations of our models in the physical world (capabilities and safety), developing new features on MHS, etc. - Scale your impact to the long tail of labs through reusable cookbooks, documentation, and other assets. - Be an EMEA ambassador for Claude in the lab - you’ll both inspire and build trust with scientific audiences, from small settings to large conferences. - This role will require significant travel You Might Be a Good Fit If You Have - Hands-on experience connecting software to lab robots and instruments (liquid handlers, plate readers, scheduling software, LIMS), ideally in an automated lab. - Strong engineering skills: you can take an LLM-powered tool from prototype to production code, and write evals to measure its performance. - A scientist's instinct for how experiments work: you can spot what's worth automating, and where AI might fail or be unsafe in the physical world. - Experience working directly with external customers or partners in a technical role. - Clear written and verbal communication: you’ll write docs other labs can use without you and give talks that inspire and earn researchers' trust. - A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission. 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: £225,000 - £255,000 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.

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE We’re hiring our first SDR Manager to help build Fireworks’ business development function from the ground up. You’ll lead, coach, and grow a team of SDRs who qualify inbound interest from developers and enterprises and prospect into high-value target accounts. Together, you’ll create the pipeline that drives our Account Executive team. This is a builder role. You’ll own the team’s performance and development while designing the playbooks, systems, and AI-powered workflows behind our top-of-funnel motion. We’re looking for a hands-on, first-line leader who gets results through great coaching. They should be fluent in AI tooling and process design, let data guide their decisions, and bring a “can do” attitude to every problem. They should be excited to define how sales development works at one of the fastest-growing companies in AI. KEY RESPONSIBILITIES - Hire, onboard, and lead a team of SDRs, scaling the team as Fireworks grows - Coach reps through regular 1:1s, call and email reviews, and hands-on skill development, building a clear path from BDR to AE - Own team performance across activity, conversion rates, meetings booked, pipeline generated, and quota attainment - Build repeatable playbooks for inbound qualification and outbound prospecting, including ICP, personas, messaging, and AE handoff criteria - Partner with Marketing to quickly convert inbound and product-led signals (signups, usage, events) into qualified opportunities - Design and deploy AI workflows and automations for account research, prioritization, personalization, and reporting, freeing reps to focus on high-value conversations - Continuously audit and improve SDR processes, from lead routing and follow-up speed to sequencing and handoffs, so the team operates efficiently at scale - Build dashboards and reporting that give the team and leadership clear, real-time visibility into funnel health - Use data to find bottlenecks, run experiments, and turn insights into action quickly - Work with Sales leadership and RevOps to align on target accounts, territories, lead routing, and pipeline goals MINIMUM QUALIFICATIONS - 2–4 years of direct, first-line management experience leading SDR/BDR teams - A proven track record of exceptional coaching and development, with reps promoted into AE or leadership roles and teams that consistently hit or exceed targets - Strong AI tooling and process skills, with hands-on experience building AI workflows that measurably improved sales productivity (e.g., Clay, AI agents, LLM-based prompts and automations) - A data-driven “can do” mindset: you dig into the numbers, spot what’s broken, and fix it yourself rather than waiting for a solution - Experience managing team performance through metrics, funnel analytics, and pipeline forecasting - Prior experience as an individual contributor in sales development or a closing role - Excellent communication and organizational skills, and comfort engaging technical buyers PREFERRED QUALIFICATIONS - Experience building a sales development function from scratch at a high-growth startup - Background in AI, developer tools, cloud infrastructure, or other technical SaaS - Experience with both high-volume inbound and targeted outbound motions - Fluency with a modern GTM stack (e.g., Salesforce, Outreach, Apollo, LinkedIn Sales Navigator, Gong) - Passion for developing early-career sales talent and an active interest in the AI/ML space Fireworks AI’s goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Large teams of agents are starting to solve problems no single agent can, from rewriting major codebases to formalizing landmark mathematics. Our team studies how these teams scale: what happens to performance, cost and coordination as the number of agents, the compute budget and the length of the task grow, and what has to change to keep getting returns from that scale. We build the platform and evaluations Anthropic uses to run and measure large agent teams, and other research teams build on them. This role lives at the boundary between research and engineering. It is a generalist role on a small team: you'll design and run large experiments, build the systems they run on, and get to the bottom of surprising results. We often need to go from a vague question to a running experiment quickly. Responsibilities: - Design, run and interpret large-scale experiments on agent teams, reasoning rigorously about what the data does and doesn't show - Investigate how performance and efficiency change as team size, compute and task horizon grow, and find the bottlenecks that limit them - Build and scale the systems that run very large agent teams reliably, and debug the failures that only appear at scale - Design evaluations for long-horizon problems, and keep their results trustworthy - Build the tooling and metrics that let researchers see what a large agent team is doing and why - Partner with research teams across Anthropic so they can run their own experiments on the platform, and communicate findings clearly You may be a good fit if you: - Have significant software engineering, ML or research engineering experience - Have owned something substantial end to end, such as a large system, an evaluation or benchmark, an agent product, or a research project - Genuinely enjoy both research and engineering work - Think quantitatively about complex systems, and think twice before trusting a number - Can work from a vague question rather than a spec - Are results-oriented, with a bias towards flexibility and impact - Have clear written and verbal communication - Care about the societal impacts of your work Strong candidates may also have: - Experience building or operating large-scale distributed systems, such as schedulers, sandboxed code execution, or inference and RL infrastructure - Built evaluations, benchmarks or harnesses for LLMs or agents - Experience building complex agentic systems that use LLMs - Experience with scaling laws or other large-scale empirical research - A background in operations research, statistics, economics, physics, quantitative finance, or another field that models and optimizes complex systems Strong candidates need not have: - Formal certifications or education credentials - Academic research experience or publication history - Prior experience with multi-agent systems or reinforcement learning Representative projects: - Measure how performance scales with the number of agents on a hard problem, and explain where the curve bends and why - Prepare our largest-ever agent run: find what breaks as team size and task length grow together, and fix it before launch - Work out how to allocate a fixed compute budget across a team of agents to solve a problem fastest - Build tooling that turns the activity of a large agent team into something a researcher can read in minutes - Design a novel eval that distinguishes real gains in teamwork from artifacts of the evaluation setup 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.

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

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About The Job Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision. What you will do - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback How We Work in Applied AI - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it. About you - You are fluent in English - You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have strong technical coding skills in Python - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have: - Contributed to open-source projects in particular in the space of LLMs - Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager - You have experience with deep learning with Pytorch Why join us? You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you! What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

About The Role We're looking for a software engineer, reliability-minded but still a builder, to own what happens in production to the Kubernetes-native control plane that provisions and runs our GPU inference fleet. The platform team builds the manifest-driven API and controllers that let the inference team declare what they need, a cluster, a model deployment, a capacity change, and get it reconciled underneath. Your job is to keep that promise true in the real world: triaging InfiniBand issues when prefill and decode nodes stall exchanging KV cache over RDMA, diagnosing hero-model and LoRA-serving faults that don't show up in generic health checks, and extending the automated self-healing system so each new failure mode becomes a permanent fix instead of a recurring page. The core value we're after is keeping the decoupling real even when things break, and keeping the fleet efficient without that efficiency becoming a new source of instability. You'll own SLOs and error budgets for inference serving, lead incident response, and turn what postmortems teach you into actual changes in the controllers and automation, not just updated runbooks. You'll also work the reliability side of capacity efficiency, since a mistuned defragmentation or bin-packing pass is itself a production risk. Strong candidates have hands-on production-reliability experience on large-scale distributed or GPU-serving systems, are comfortable troubleshooting InfiniBand/RDMA and Kubernetes controller/CRD-based platforms, and think about GPU infrastructure, and the tools that keep it reliable, as software to be engineered. A product mindset applies: the on-call experience, the clarity of an alert, and the judgment built into an automated remediation are things you ship and iterate on. Responsibilities - Operate the provisioning state machine in production: own the health of the host lifecycle pipeline, discovery, inference bring-up, GPU driver/CUDA validation, health checks, decommission/RMA, triaging stuck or failed state transitions at fleet scale and feeding real failure patterns back into how the states and transitions are designed. - Triage and extend automated self-healing: when the node-scanning and remediation platform misses something, a new failure mode, an InfiniBand issue in disaggregated prefill/decode serving, a GPU Xid variant, a hero-model or LoRA-specific fault, diagnose it live, drive the fix to production, and turn it into a new detection/remediation plugin so it's automatic the next time. - Own end-to-end reliability of the pipeline: hold the SLOs and error budgets for provisioning and fleet health, lead incident response when idempotency, retry, rollback, or drift assumptions break down in practice, and drive the systemic fix, not just the hotfix. - Partner with the inference/ML platform team from the production side: be the one who knows how real cluster topologies, interconnects, and scheduling constraints actually fail in the field, and feed those failure modes back as first-class requirements into the platform's abstractions. - Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production, enabling advanced research through awesome engineering. - Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. - Build tools to give us visibility into our bottlenecks and sources of instability, then design and implement solutions to address the highest-priority issues. - Lead reliability cross-functionally: build coalition across infra, ML platform, and product teams around shared reliability priorities, manage stakeholders through incidents and roadmap trade-offs, and represent the reliability point of view in planning so it shapes decisions before they ship, not after an outage. Requirements - Experience operating a provisioning or host-lifecycle pipeline in production, comfortable troubleshooting stuck or failed state transitions (discovery, bring-up, GPU driver/CUDA validation, health checks, decommission/RMA) at fleet scale, and translating real failure patterns back into improvements to the state machine’s design. - Deep experience owning production reliability for large-scale distributed systems; GPU/ML-serving infrastructure experience is a strong plus. - Hands-on experience troubleshooting InfiniBand/RDMA networking issues, ideally in a multi-node training or disaggregated-inference context — comfortable reading IB port counters and subnet manager logs, not just application metrics. - Familiarity with the operational realities of multi-tenant model serving (LoRA/adapter-based serving) and with running differentiated SLOs across model pools of different priority. - A demonstrated track record of eliminating operational toil through automation and tooling you built yourself, not just process or documentation. - Hands-on experience with Kubernetes controller/CRD patterns, reconciliation loops, and node-level health/remediation systems. - Comfort with event-driven architectures, backpressure/circuit-breaking design, and treating observability (metrics, logs, traces) as something built into a system, not added after an incident. - A software-engineering mindset first: you write and ship production code, and you think about GPU infrastructure as software to be engineered, not a fleet to be manually operated. About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $250,000 - $320,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy .

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About The Job Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision. What you will do - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback How We Work in Applied AI - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it. About you - You are fluent in English - You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have strong technical coding skills in Python - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have: - Contributed to open-source projects in particular in the space of LLMs - Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager - You have experience with deep learning with Pytorch Why join us? You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you! What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

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

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About The Job: Mistral AI is seeking a Technical Lead, Applied AI to drive the technical strategy, execution, and delivery of complex AI solutions for our enterprise customers. In this role, you will lead a project teams of Applied AI Engineers, ensuring the successful deployment of Mistral AI products and the development of high-impact, scalable AI use cases. You will act as the primary technical point of contact for our most strategic customers, guiding them through the entire lifecycle—from pre-sales to post-implementation—while collaborating closely with research, product, and engineering teams to shape the future of our offerings. As a Technical Lead, you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral’s technological vision. What you will do - Deliver as an IC the critical lines of codes of our complex projects , you’ll be hands-on and de-risk the critical parts of our complex projects. You’ll stay deeply involved in coding, reviewing, and optimizing AI solutions. - Lead technical teams of Applied AI Engineers , providing mentorship, technical guidance, and best practices for deploying state-of-the-art GenAI applications across industries. - Lead technical discussions during pre-sales , translating customer requirements into actionable solutions and communicating Mistral’s technological advantages to diverse stakeholders. - Design and oversee the implementation of complex AI systems , including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap and open-source initiatives. - Drive innovation by identifying emerging trends in AI , evaluating new tools and methodologies, and championing best practices for fine-tuning, inference, and deployment. - Work closely with product managers, researchers, and engineers to ensure seamless integration of customer feedback into Mistral’s product development cycle. How We Work in Applied AI - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it. About you - You are fluent in English. - You hold a PhD or Master’s degree in AI, Machine Learning, Computer Science, or a related field. - You have 7/8+ years of experience in AI/ML, with at least 2+ years in a technical leadership role (e.g., Tech Lead, Engineering Manager, or Solutions Architect) focused on AI products or enterprise solutions. - You have a proven track record of leading teams to deliver complex AI projects, from prototyping to production, in industries such as tech, finance, healthcare, or industrial automation. - You possess deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale. - You are proficient in Python, PyTorch , and modern AI frameworks (e.g., LangChain, Hugging Face). Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools is a plus. - You have strong software engineering skills , including API design, backend/full-stack development, and system architecture. - You excel in technical communication , with the ability to articulate complex concepts to both technical and non-technical audiences, including executives and engineers. - You thrive in fast-paced, collaborative environments and are passionate about mentoring and growing technical talent. Ideally, you have: - Contributed to open-source projects, particularly in the LLM or AI space. - Experience in customer-facing roles (e.g., Solutions Architect, Customer Engineer, or Technical Product Manager) with a focus on enterprise AI adoption. - A track record of driving technical strategy and influencing product direction based on customer needs and market opportunities. Why join us? You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you! What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

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 International Policy Applied AI team at Anthropic, you will be a trusted technical advisor to governments, AI Safety Institutes (AISIs), and multilateral institutions. You'll use your technical skills and your experience with government partners to help them understand frontier AI, test it, and apply it to their public missions with a high degree of reliability and safety. This role serves Anthropic's policy, mission, and public benefit goals. In collaboration with the Policy, Product, Research, and Engineering teams, you'll help partners develop strategies and plans to evaluate and adopt leading-edge AI systems. You will use your excellent communication skills to explain complex topics, including the potential benefits and harms of frontier AI, to technical and non-technical audiences alike. You will also play a critical role in identifying how our AI systems can best serve public interests around the world, while maintaining our best-in-class safety standards. Responsibilities: - Act as a primary technical advisor for senior officials in partner governments, AISIs, and international institutions. Brief them on frontier AI capabilities, give an honest account of both benefits and harms, and explain safety research in terms that inform their decisions. - Partner closely with the Policy team to understand each partner's goals and requirements. Develop demos, pilots, prototypes, and evaluation suites that show how Claude can support their public missions, such as cyber defense. - Lead technical onboarding, enablement, and hands-on workshops for partner institutions, including national cybersecurity agencies. Guide their setup, architecture, and integration as they build with Claude Code and the Claude API. - Act as the voice of our international partners and a key collaborator with our Product and Research teams to ensure we deliver the capabilities they need. - Travel internationally to partner institutions for senior leader meetings, 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: - 4+ years of experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Cybersecurity Engineer, working with governments, international organizations, or the public sector - Experience in technology policy, AI safety, cybersecurity, or international affairs - Designed novel and innovative solutions for technical platforms in a developing mission area - Familiarity with how AI models are evaluated and tested for safety - 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 problem at hand, finding simple, easy-to-understand solutions - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders, from engineers to senior government officials - 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: $240,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. For software engineering organizations, this means helping customers adopt Codex and other OpenAI capabilities across the software development lifecycle—transforming how teams plan, build, test, review, and deliver software. We work directly with engineering leaders and hands-on developers to identify high-value opportunities, design and implement AI-powered development workflows, and scale what works across engineering organizations. We turn lessons from these deployments into better products, reusable architectures, and technical patterns that help developers everywhere get more value from Codex. About the Role As an Applied AI Engineer focused on Codex, you will partner directly with leading engineering organizations to design, build, and deploy AI systems that transform how software is developed. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from workflow and use-case selection through prototyping, evaluation, production rollout, and scaled adoption. You will work alongside engineering teams to build advanced AI coding workflows, integrations, automations, and evaluation systems—often using Codex itself as part of your development process. You will help customers make technical decisions involving model behavior, agentic workflows, developer environments, security, reliability, evaluation, and operational readiness, while ensuring deployments translate into measurable improvements in engineering productivity and software delivery. You will work closely with OpenAI Product, Research, Engineering, Security, Sales, and the broader Codex organization, translating real-world deployment experience into high-signal product and model feedback. Success is measured by production systems, sustained developer adoption, and meaningful improvements to how engineering organizations build software—not simply successful demonstrations or enablement activity. This role is based in our Madrid office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Partner directly with engineering leaders and hands-on developers to identify high-value opportunities for Codex and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. - Design, build, and deploy AI-powered software development workflows that improve how engineering teams plan, write, test, review, debug, and deliver software. - Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, workflow automations, and production accelerators—often using Codex as part of your own development process. - Help customers progress from promising experiments to reliable production workflows, sustained developer adoption, and scaled impact across engineering organizations. - Design systematic approaches for evaluating AI coding systems using representative software engineering tasks, automated graders, production signals, and developer feedback. - Make sound technical decisions across models, agents, tools, developer environments, integrations, reliability, observability, latency, cost, safety, security, and operational readiness. - Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive technical blockers toward resolution. - Lead technical deep dives, workshops, and hands-on enablement that help engineering teams understand and adopt advanced AI coding workflows effectively and safely. - Gather high-fidelity insights from real-world Codex deployments and translate them into clear product proposals, model feedback, and technical requirements for OpenAI Product, Research, and Engineering teams. - Create reusable architectures, tooling, examples, guides, and technical patterns—including contributions to resources such as the OpenAI Cookbook—that accelerate future Codex deployments. - Influence customer engineering strategy by helping technical leaders understand how AI coding systems can reshape their software development lifecycle, engineering practices, and organizational workflows. You’ll thrive in this role if you: - Have a demonstrated track record of designing, building, and delivering software or AI systems in enterprise environments, including taking systems from prototype to production. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, developer tooling, customer engineering, solutions architecture, or technical consulting. - Can point to substantial personal contributions in code, architecture, evaluation, debugging, integrations, or production engineering—not only program, enablement, or stakeholder management. - Are highly proficient in Python and comfortable working across modern software development environments; experience with JavaScript, TypeScript, or another relevant language is valuable. - Are an active user of AI coding tools and have developed a strong point of view on how AI can improve developer productivity and software engineering workflows. - Enjoy building high-signal prototypes, integrations, automations, and production solutions that demonstrate and deliver what AI coding systems can enable. - Understand how to evaluate AI coding systems systematically, including designing representative tasks, automated evaluations, production signals, and mechanisms for incorporating developer feedback. - Have navigated enterprise production requirements such as developer tooling integrations, reliability, observability, security, privacy, data governance, performance, and cost. - Can connect technical decisions to developer workflows, adoption, engineering productivity, and measurable business outcomes. - Communicate with clarity and credibility across hands-on engineers, engineering leaders, security teams, product leaders, and executives. - Are comfortable leading technical workshops and hands-on sessions that help engineering organizations adopt new development workflows and technologies. - Bring high agency, strong technical judgment, and end-to-end ownership in ambiguous and rapidly evolving environments. - Learn quickly, challenge assumptions constructively, and collaborate with humility; deep prior experience with OpenAI products is not required. - Are able to speak English and Spanish fluently. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. As Office Manager, you run our New York office and make it a place people want to come to. The office is open, but the operational foundation is still to be built: few local vendors, no established rhythm, and a team growing fast. You run the office day to day as it grows from a handful of people to a full regional site, and you help put the foundation underneath it. Day to day, you are the person who makes the office work: the space, the vendors, the onboarding, the events, the visitors, and the hundred small things that decide whether a team is set up to do its best work. You also set the atmosphere. A lot of what makes an office somewhere people choose to be comes down to who runs it. This is an in-office role in New York, and you will be at the office five days of the week. It suits a hands-on operator who likes being first in: equally comfortable pushing a vendor contract over the line and sorting the catering order, and proud of a team that never has to think about logistics. We care more about how good you are than how many years you have done this. If you are early in your career but have a clear record of excelling at whatever you took on, we want to hear from you. Key Responsibilities - Office: Run our New York office end to end: the relationship with the landlord or workspace provider, access and security, health and safety, the cleaning and facilities vendors, supplies, and the day-to-day running of the space. - Atmosphere and Team Rhythm: Own the office cadence, from lunches and all-hands setup to team dinners and offsites. For customer and community events, partner with our Field Marketing team, who own the programmes, ensuring everything hosted at the office runs smoothly. - Onboarding: Make every new joiner productive on day one: equipment, access, desk, local paperwork, and a proper welcome. Handle offboarding just as cleanly. - Visitors: Host visiting executives, customers, and candidates, and make sure their time at the office runs smoothly. - Vendors and Budget: Select and manage local vendors (landlord or workspace provider, IT and device provisioning, AV, catering, cleaning, security, insurance) and own the office budget, invoices, and renewals. Minimum Qualifications A demonstrable record of excellence in whatever you have done so far (office management, operations, a startup, a fast-paced team, or elsewhere), where you were clearly one of the best at it. Years of experience matter less than this. - Fast learner with real curiosity: comfortable learning new skills that may be needed in the office with no clear owner, and knowing when to bring in expert help. - Hands-on with vendors and negotiation, or the confidence and judgment to become so quickly. - Highly organised, with a track record of running many parallel workstreams to completion without being chased. - Comfortable operating with autonomy in an ambiguous, fast-changing environment; you build the process rather than wait for it. - Excellent written and verbal communication and a service mindset toward the team. - Warm, calm under pressure, and the kind of person people go to first. This role sets the tone of the office. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role Mistral AI is seeking Applied Scientists and Research Engineers focused on formal methods. You will design, train, and deploy SOTA large language models and apply them to diverse use cases. You'll work cross-functionally with internal and external science, engineering, and product teams to deliver high-impact AI solutions. What You Will Do - Run pre-training, post-training and deploy state of the art models on large clusters. - Generate and curate datasets for theorem proving and software verification, and build evaluators and benchmarks for formal reasoning. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. What We're Looking For - Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences. - Expert with PyTorch or JAX. - Not afraid of contributing to a big codebase; finds their way around independently with little guidance. - Writes clean, readable, high-performance, fault-tolerant Python code. - Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. Nice to have - PhD / Master in a relevant field (Computer Science, Mathematics, Machine Learning). - Experience with autoformalization, proof automation, or verified code generation. - Experience with reinforcement learning using verifiable rewards, ideally from Lean or other proof assistants. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. We are looking for a Senior Principal AI Solutions Engineer: a hands-on technical leader who sets the technical direction for our solutions portfolio and still builds. This is someone who can go from a customer problem to a polished, working, agentic application in days, and then harden it for production. You will work across the whole modern AI stack: open-weight models, agent frameworks and tool use, self-improving evaluation loops, multimodal and voice pipelines, and the front end that makes it all usable by knowledge workers. You will lead hands-on engagements with our most strategic customers, mentor and raise the bar for the wider solutions team, and feed what you learn back into the platform. Responsibilities Build agentic and self-improving systems - Agentic AI Architecture: Design and build single- and multi-agent systems with planning, tool and function calling, MCP, memory, and long-running workflows that are reliable enough for production • Self-Improving Systems: Build feedback loops that make agents better over time, including automated evals, LLM-as-judge, trace-driven prompt and program optimization (e.g. DSPy-style), synthetic data generation, and fine-tuning from production signals - Evaluation and Observability: Set up eval harnesses, tracing and guardrails so customers can measure quality, cost and latency, and trust what they deploy Get the most from open models - Open-Weight Model Expertise: Choose, adapt and combine open models (e.g. Llama, Qwen, DeepSeek, gpt-oss, Gemma, GLM) for customer use cases, including LoRA/PEFT fine-tuning, distillation and model routing - Performance and Benchmarking: Benchmark end-to-end solutions, not just tokens per second, and show where fast inference changes what an application can do - Model Integration: Validate new models and capabilities on SambaNova's platform stack and report gaps to Product and Engineering Ship full-stack vertical solutions - Front-End and Product Build: Build polished, usable web applications (e.g. React/Next.js, TypeScript) that non-technical knowledge workers can adopt, not just notebooks and APIs - Vertical Knowledge Work: Build domain solutions for areas such as financial services, legal, healthcare, public sector and research: document analysis, research agents, RAG and knowledge assistants, report generation and workflow automation - Multimodal Solutions: Build vision-language and document-understanding pipelines (OCR, charts, forms, images, video) combined with agentic reasoning - Audio and Voice: Build real-time voice agents and audio pipelines (ASR, TTS, speech-to-speech, streaming and turn-taking) where low latency is the product Lead with customers and shape the platform - Solutions Technical Strategy: Set the technical direction for the solutions portfolio: which agentic, multimodal and vertical patterns we invest in, the shared frameworks and components we build, and the engineering standards they meet - Technical Leadership and Mentorship: Act as the senior technical authority across solutions engineering; review designs, mentor engineers and lift the quality of everything the team ships - Executive Engagement: Act as the trusted technical advisor to customer CTOs and AI leaders on architecture, build-versus-buy and scaling AI across the enterprise - Customer Engagement: Lead technical discovery, workshops, hackathons and hands-on co-builds with strategic customers, from prototype to production - Reference Architectures: Publish reference architectures, starter kits, open-source examples and best-practice guides that scale beyond each engagement - SambaStack Tooling: Develop tooling and automation for SambaStack deployment, management and integration - Product Feedback: Feed what you learn in the field (model requests, feature gaps, developer experience) into the model roadmap and platform priorities - Thought Leadership: Represent SambaNova through demos, talks, blogs and community contributions Requirements Required Qualifications - Bachelor's degree or higher in Computer Science, Electrical Engineering, Applied Mathematics, Physics, Statistics or a related field - 8+ years (IC5) or 10+ years (IC6) of industry experience in software, ML or solutions engineering, including 3+ years building LLM-based applications that reached production - Proven experience building agentic systems: tool and function calling, multi-agent orchestration and frameworks such as LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK or equivalent • Hands-on experience with open-weight models: serving, prompting, fine-tuning (LoRA/PEFT) and evaluation • Strong full-stack skills: expert Python plus modern front-end development (TypeScript, React/Next.js), APIs and cloud deployment - Experience designing evals and benchmarks for LLM applications, covering quality, latency and cost • Excellent customer communication, with the ability to lead workshops and explain architecture to both executives and engineers - A track record of technical leadership across teams: setting architecture direction, mentoring senior engineers and owning outcomes for strategic accounts Preferred Qualifications - Experience building self-improving or learning systems: prompt/program optimization, RL from feedback, synthetic data pipelines or continual fine-tuning - Experience building real-time voice agents (e.g. LiveKit, Pipecat, WebRTC) and working with speech models (ASR/TTS) - Experience with multimodal and vision-language models and document-understanding pipelines • Domain experience in one or more knowledge-work verticals (financial services, legal, healthcare, public sector, scientific research) - Familiarity with inference frameworks (vLLM, SGLang, TensorRT-LLM) and hardware-aware performance tuning - Experience with MCP, RAG at enterprise scale, and agent security and guardrails • Open-source contributions, public demos or technical content in the AI community Base Salary Range: Base Pay Range $234,000 - $286,000 USD Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified. EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

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

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 customer-facing teams are often the first place a customer sees what Claude can do. As a Demo Engineer, you'll build the demos, reference implementations, and reusable tooling that help those teams make new capabilities tangible, relevant, and trustworthy, ideally within days of a product launch rather than weeks after. This role sits between product engineering, technical storytelling, and GTM execution. You'll own ambiguous, high-leverage problems end to end: prototyping an agentic experience for a new capability, then hardening it into something reliable that other teams can run on their own. You'll work closely with Product, Engineering, Marketing, Operations, and our sales and solutions teams, and you'll bring what you learn from customer-facing work back to the people building the products. Because a demo is frequently someone's first impression of what our models can and can't do, accuracy and honesty matter as much as polish. Success in this role looks like customer-facing teams demonstrating new capabilities sooner and with more confidence, recurring requests becoming reusable assets rather than one-off projects, and field insights shaping product and launch-readiness decisions. Responsibilities - Own demo readiness for new and priority Claude capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths - Build prototypes, agents, and reference flows that make complex capabilities concrete and tie them to clear customer outcomes - Turn recurring requests into reusable accelerators such as companion apps, templates, Skills, plugins, and self-service demo packages that scale across customer-facing teams - Partner with GTM colleagues on high-impact customer moments, unblock critical technical gaps, and spot the patterns worth turning into shared assets - Build internal agentic systems that automate demo preparation, validation, and asset maintenance, so demos stay current as products change - Translate patterns from customer-facing work into product feedback, launch-readiness priorities, and systemic improvements with Product and Engineering - Define and raise the bar for demo quality across accuracy, safety, reliability, usability, and adoption - Decide when a customer need calls for a bespoke build and when it should become a shared capability You may be a good fit if you have - Proficiency in Python or TypeScript, with experience shipping working software end to end - Hands-on experience building applications or agents on top of LLM APIs, including prompting, tool use, and retrieval - Experience designing integrations with third-party APIs, data sources, and services - The ability to take an ambiguous capability or customer need to a working prototype quickly, and then make it reliable - Clear communication of technical concepts to both technical and non-technical audiences, including sales and solutions teams - Comfort collaborating across Product, Engineering, Marketing, Operations, and GTM teams - Experience in a demo engineering, solutions engineering, sales engineering, forward deployed engineering, developer relations, or product engineering role - A track record of building reusable internal tools, templates, or self-service assets that other teams adopted - Hands-on experience with Claude Code, the Claude Agent SDK, the Model Context Protocol (MCP), Skills, or plugins - Experience building evaluation or validation harnesses for AI systems, including reliability checks and graceful fallbacks - Experience building always-on or scheduled agentic systems that automate internal workflows - Experience building synthetic or sanitized datasets that make demos realistic without exposing sensitive information - Front-end or product design skills that help demos feel polished and intuitive - Experience supporting product launches or running launch-readiness programs - A history of turning field feedback into concrete product input that influenced a roadmap - A passion for making powerful technology safe and beneficial, and a commitment to representing model capabilities accurately and honestly 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: $240,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

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 At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications. Claude is getting good at research. Given a well-posed problem, it can read the literature, write and run simulations, analyze results, and iterate on a design across physics, materials, chemistry, and engineering. But most of the hardest problems in science and engineering aren't well-posed. They live inside companies and labs with their own data, tools, constraints, and experts, and progress depends on turning all of that into work a model can actually do and check. Our Applied AI, Science & Engineering team takes Claude to the scientists and engineers working on hard problems in energy, materials, hardware design, and other physical-world fields. We build the tools Claude needs to do real research and engineering work. Mostly that means software: the agent harnesses, integrations, evaluations, and working processes that turn a partner's problem into something Claude can make progress on and validate. We find real-world problems and test what we build through partner engagements, then feed our learnings back to our research and product teams. It's early, and the engineers who join now will shape how Claude gets applied to science and engineering. This is an engineering role first. You'll spend real time with domain experts, become the person who knows how to get Claude working in their field, and prototype quickly alongside them. Most of your time, though, goes into building and hardening the systems that make that work repeatable, not into writing recommendations or configuring someone else's product. A science or engineering background is a big plus, but what matters most is that you can earn the trust of expert researchers, turn a fuzzy problem into something concrete and checkable, and ship. Responsibilities - Build the agent harnesses and research loops that let Claude carry a problem from literature review through hypothesis generation, simulation, analysis, and design iteration - Connect scientific computing and simulation tools (finite element, CFD, electromagnetic, or molecular modeling codes, for example) so Claude can drive them reliably and at scale - Design and build evaluations that tell us whether Claude's work is actually right, and be honest about where it isn't - Sit with scientists and engineers at partner organizations to learn their problem, data, tools, and constraints, and turn open-ended questions into well-specified, verifiable tasks with clear success criteria - Prototype with partners, ship pilots into their workflows, and cut anything that doesn't move the problem forward - Turn what works in one engagement into shared tools, reusable components, and documented processes the next one can start from - Be the technical voice on how Claude performs on science and engineering work, explaining results, limits, and tradeoffs clearly to researchers, engineering leads, and non-technical stakeholders alike - Partner with our research and product teams to share where models fall short on science and engineering work, and help shape what comes next You may be a good fit if you - Have 8+ years of experience building software, with strong engineering fundamentals and comfort across the stack, from data pipelines to tooling to quick interfaces - Have built real systems with large language models, including agents, tool use, or evaluations - Have worked on technical problems in a science or engineering field, such as physics, materials, chemistry, or electrical or mechanical engineering - Have a track record of zero-to-one work in startup or startup-like environments\ - Can work directly with expert users, understand their workflows deeply, and still keep the focus on building the right system rather than the one first requested - Have good judgment about what can and can't be verified, and are comfortable saying a result isn't good enough yet - Bring high agency, pick up new domains quickly, and hold strong opinions loosely - Communicate clearly with researchers, engineers, and external partners, and care about the societal impacts of your work Strong candidates may also have - An advanced degree or research experience in a physical science or engineering field - Hands-on experience with scientific computing and simulation, numerical methods, or optimization - Experience in industrial R&D, a national lab, or a deep-tech company in areas like energy, materials, manufacturing, or hardware - Experience building alongside customers or technical partners, for example in forward-deployed, applied AI, or solutions engineering roles, ideally where you also owned the software that came out of it - Experience with ML research, RL environments, or evaluation design Candidates need not have - 100% of the skills listed above - Formal certifications or education credentials - Expertise in every scientific domain we work in - Direct machine learning or AI research experience 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 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Claude Partner Network (CPN) Reseller track lets authorized partners sell Claude directly to end customers. These partners bring Claude into accounts that Anthropic can't reach alone, and they need marketing that helps them build a real Claude practice: campaigns they can run with their own teams, funding they can put to work, and proof that moves them up through the partner tiers. This is a foundational, first-in-seat role with wide scope. You'll be the first dedicated partner marketer for the reseller track, and you'll lead it globally. You'll set its marketing strategy, define the standards and playbooks partners run against, and build the tier-advancement path from the ground up. You'll work across regions and with a network of agency partners to deliver programs at global scale. You'll shape how reseller marketing fits into Anthropic's broader partner strategy, working with Partnerships, Commercial Operations, Channel Account Managers, Partner Operations, Customer Marketing, and Communications to make sure reseller activity and Anthropic's direct sales point in the same direction. You'll also set the bar for the marketers who join the practice as it grows. Key responsibilities - Set the marketing strategy for the reseller track, including priorities, investment choices, and quarterly and annual plans that connect partner activity to registered pipeline and reseller revenue - Define the reseller marketing playbook and co-marketing standards, and keep them current as the program launches and expands - Represent the partner marketing perspective in program design, working with Partnerships, Commercial Operations, and Legal on how benefits, MDF, and tier criteria will work in practice - Build joint marketing plan templates for reseller partners, including campaign calendars and success metrics - Source, select, and manage the agency partners that support reseller programs globally, including scope, budgets, quality standards, and performance reviews, and build a regional roster that can scale as the program expands - Run partner-led campaigns with those agencies, using co-branded and localized kits for each market, and help partners adapt them for their own buyers - Own partner marketing funds (MDF) end to end: help partners build proposals, track approvals and documentation, and connect every funded activity to registered pipeline - Help partners reach their next tier by planning the customer stories, certification pushes, and public proof points each tier requires, on a timeline that fits the January and July tier reviews - Turn partner wins into customer stories with Customer Marketing, from interview through partner and Anthropic approvals - Coordinate joint announcements and press with Anthropic Communications, managing review timelines and holding partner copy to Anthropic's messaging and brand standards - Partner with Channel Account Managers and the field on audience and account targeting, so reseller campaigns extend Anthropic’s reach into new customers and partner and direct motions reinforce each other - Define how reseller marketing success is measured: set targets and KPIs for pipeline, reseller revenue, and campaign ROI, build the reporting, and use results to decide where to invest and what to change - Report on partner-sourced pipeline and reseller revenue influence, with 30/60/90-day tracking on every activation - Keep reseller partners informed through the CPN monthly broadcast and newsletter, and bring partner needs and results back into program planning Minimum qualifications - Have owned marketing strategy for a partner or channel program, setting priorities and investment decisions rather than only executing against them - Have built and run co-marketing programs with channel, reseller, or distribution partners, including partner-funded budgets (MDF, co-op, or similar) and ROI reporting - Have sourced and managed agencies or contractors across multiple regions, including scoping work, managing budgets, and holding quality standards - Have run marketing programs across multiple international markets - Understand indirect sales motions, including how partners find, register, and close deals, and can write marketing that reaches partner sellers as well as end customers - Can build joint plans and value propositions that articulate clear business outcomes for customers - Have defined success measures for a partner or channel program and used the results to change investment decisions - Are skilled at tracking program performance in a CRM or equivalent system, and can turn that data into clear recommendations - Write clearly and precisely, and can hold partner-produced copy to brand and approval standards - Build trusted relationships with partner marketing and sales teams, and can move priorities forward with partners you don't manage - Can make and defend decisions with incomplete data, and know when to escalate - Are highly organized and can run several partner plans at once without dropping quality - Are comfortable building new processes from scratch, in an environment where the playbook is still being written - Take ownership of outcomes and step in wherever the work needs you - Care about the societal impacts of AI and are excited about enabling organizations to adopt AI responsibly Preferred qualifications - Have 7+ years of marketing experience, with significant focus on partner marketing in B2B technology environments - Have launched or scaled a partner program from its early stages, including tier design, benefits, and promotion criteria - Have produced partner-led customer stories, including managing approvals and public announcement timelines - Have experience with cloud marketplace reseller motions, such as private offers or co-sell programs - Have localized marketing content and campaigns for multiple international markets - Have established relationships with resellers, distributors, or systems integrators - Have experience with partner relationship management tools and Salesforce partner data - Understand enterprise AI use cases across industries and functions - Have set standards for or mentored other marketers, formally or informally - Have used Claude or other AI tools to scale their own marketing work 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 - $400,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About 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 Manager of the EMEA Digital Natives Applied AI Architecture team, you'll drive adoption of frontier AI across Europe's fastest-growing technology companies: SaaS scale-ups, fintechs, marketplaces, consumer platforms, and developer-tooling businesses. Your team makes Anthropic's products (Claude Enterprise, Claude Code, and the Claude API) successful in production. They address each customer's business needs and technical requirements, and they meet the high bar for reliability and safety that these companies' own users expect. You'll lead and grow a team of Applied AI Architects across EMEA. You'll set the pre-sales standards for the segment, develop each person on the team, and act as a technical lead on some of Anthropic's most strategic European accounts. You'll work closely with Sales, Product, and Engineering to help digital-native companies build Claude into their core products and platforms. You'll also explain complex solutions clearly to both engineers and executives. Responsibilities - Manage and mentor a distributed team of Applied AI Architects, providing technical guidance and career development - Set goals and run performance reviews that drive growth and output - Work directly with a small number of the highest-value EMEA digital-native customers on their AI adoption strategy, including: - use case scoping - building technical champions - running POCs - Partner with EMEA GTM leadership to understand customer requirements and co-build segment strategy - Own the technical side of pre-sales, making sure your team delivers compelling demos and validates customer ROI - Guide customers through EMEA-specific technical and procurement requirements, including GDPR, the EU AI Act, and data residency - Align cross-functional stakeholders across time zones and regions to drive business outcomes - Travel regularly across EMEA for executive sessions, technical workshops, and relationship building - Lead the vision and execution of solutions that use our latest models for tech-forward use cases - Represent Anthropic in the European tech community through conferences, meetups, webinars, and technical content - Stay current on AI/ML developments and the competitive landscape in the European tech sector You may be a good fit if you have - 7+ years of experience as a Solutions Architect, Sales Engineer, or in a similar pre-sales technical role - 3+ years of experience managing pre-sales or technical GTM teams, ideally across multiple EMEA markets - Experience selling to and working with digital-native companies, such as vertical or horizontal SaaS, consumer tech, fintech, PaaS, or developer platforms - Familiarity with how European tech companies evaluate and procure technology, including security reviews, DPAs, and regulatory scrutiny - Deep technical proficiency with API integrations, production LLM use cases, and AI-powered system architecture - Hands-on experience with prompt engineering and LLM evaluation, plus working knowledge of how large language models are built and operate - A strong grasp of developer tooling, SDKs, and the integration patterns common in modern software companies - Enjoyment of building foundational teams in unstructured, fast-moving environments - Strong executive presence and the ability to build deep trust with CTOs, engineering leaders, and technical founders - Excellent communication, collaboration, and coaching skills - The ability to make ambiguous problems clear and find principles that carry across scenarios - A passion for making powerful technology safe and beneficial, with a habit of thinking beyond past checklists and playbooks 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: £190,000 - £230,000 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.

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 Solutions Architect on the Startups Applied AI team at Anthropic, you will win the trust of founders and engineers by being an exceptional technical partner, helping startups successfully build on the Claude Developer Platform as they grow from early product to scale. You'll combine deep technical expertise with a builder-first mindset to help startups architect innovative LLM solutions, win technical evaluations, and get the most out of Claude. Working closely with Account Executives and the broader Sales, Product, and Engineering teams, you'll guide startups from initial technical discovery through successful deployment and beyond. You'll leverage your expertise to help founders understand Claude's capabilities, develop evals, and design architectures that maximize the value of our AI systems. Responsibilities: - Partner with Account Executives to deeply understand startup requirements, translate them into technical solutions, and serve as a trusted technical advisor throughout the Claude adoption journey from initial evaluation through deployment and expansion - Win technical evaluations that demonstrate why Claude is the best foundation for what startups are building, helping them develop evaluation frameworks to measure Claude's performance for their specific use cases - Build technical credibility with founders, founding engineers, and startup engineering teams by speaking their language, understanding their build patterns, and guiding technical architecture decisions - Gather insights on how startups are building with Claude, identify emerging use cases and deployment patterns, and deliver feedback to Product and Engineering teams - Travel to customer sites, startup-focused events, and industry conferences for workshops, technical deep dives, and relationship building You may be a good fit if you have: - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, Forward Deployed Engineer, or technical founder who has done founder-led sales - Experience working with startups or high-growth technology companies; you understand the velocity and constraints of early-stage companies - Strong builder credibility through experience as a software engineer or technical founder; you speak the language of builders and have the presence to earn the trust of technical founders and startup engineering teams - Deep technical proficiency with building and scaling AI products, a pulse on AI engineering best practices, and the ability to demonstrate why Claude is the best foundation - Hands-on experience building and deploying LLM-powered applications in production, with expertise in context engineering, evaluation frameworks, and modern AI architectures - Strong technical communication skills with the ability to translate complex AI concepts into actionable insights for founders and engineering teams - Track record of selling technical products in competitive markets - Comfortable with Python and familiarity with common LLM frameworks, tools, and integration patterns - Passion for making powerful technology safe and societally beneficial 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: £165,000 - £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.

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 leader of Applied AI Solutions Architecture in Japan, you will drive the adoption of frontier AI by enabling the deployment of Anthropic’s products (Claude for Enterprise, Claude Code, and API) across Japanese enterprises and digital-first organizations. You’ll leverage your technical skills and consultative sales experience to drive positive AI transformation that addresses our customers’ business needs, meets their technical requirements, and provides a high degree of reliability and safety. You’ll lead and grow a Japan Applied AI team as Anthropic’s presence in the market continues to expand. Applied AI comprises Solutions Architects, Product Engineers, and Finetuning Engineers. Working alongside the existing Japan Applied AI leadership, you will scale processes and best practices for the region’s technical pre-sales engagements, help each team member achieve success, high productivity, and career growth, and represent Anthropic as a technical lead on some of its most important partnerships. In collaboration with the Sales, Product, and Engineering teams globally and locally, you’ll help enterprise partners incorporate leading-edge AI systems into their cutting-edge products and platforms. You will employ your excellent communication skills, in both Japanese and English, to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike. You will play a critical role in identifying opportunities to innovate and differentiate our AI systems, while maintaining our best-in-class safety standards. Responsibilities - Lead and grow a team of Applied AI professionals in Tokyo (Solutions Architects and Product Engineers), providing both technical guidance and career development - Set goals and reviews for your team, promoting growth and output - Partner with the existing Japan Applied AI leadership to align on team structure, coverage, and best practices - Work with a handful of the highest-value enterprise customers on their overall AI adoption strategies, focusing on pre-sales technical excellence including use case scoping, technical champion building, and POC execution - Partner closely with your aligned GTM leadership to understand customer requirements and co-build GTM strategies to drive adoption for Japanese enterprise customers and partners (including SIers and resellers) - Contribute to thought leadership through conference presentations, webinars, and technical content creation - Own the technical portions of pre-sales engagements, ensuring your team provides compelling demos and validates enterprise customer ROI from Anthropic products - Drive collaboration across cross-functional teams to influence and unify stakeholders at all levels of the organization, including navigating consensus-driven decision-making within Japanese enterprises - Travel regularly to customer sites for executive-level sessions, technical workshops, and building relationships - Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products - Lead the vision, strategy, and execution of innovative solutions that leverage our latest models’ capabilities - Stay current with emerging AI/ML trends and the competitive landscape in the Japanese enterprise tech sector You may be a good fit if you have: - 7+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role - 3+ years of technical go-to-market management experience, specifically managing pre-sales teams - Native or business-level fluency in Japanese and professional proficiency in English - Experience working with Japanese enterprise customers and understanding local business culture and decision-making processes (e.g., ringi/nemawashi, multi-layer stakeholder alignment) - Experience with the unique technical requirements and technical procurement processes of Japanese enterprises, including working through SIers and channel partners - Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases - An organizational mindset and enjoyment of scaling teams in a fast-growing, evolving environment - Excellent communication, collaboration, and coaching abilities - Comfort with uncertain, ambiguous, and fast-moving environments typical of the tech industry - Strong executive presence and the ability to foster deep relationships with technical leaders and engineering teams - At least a high-level familiarity with the architecture and operation of large language models and/or ML in general - Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems - The ability to make ambiguous problems clear and identify core principles that translate across scenarios - A passion for making powerful technology safe and societally beneficial - Creative thinking about the risks and benefits of new technologies, beyond past checklists and playbooks - An active interest in emerging research and industry trends - Understanding of developer tooling, SDKs, and technical integration patterns common in enterprise tech companies Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

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