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Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: We're hiring several Product Operations Managers to embed within our core product teams. Each will contribute to a key component of our stack. Whether you are ensuring models work within each of our harnesses, prioritizing a great experience across cloud offerings, or building the application layer that keeps users on the frontier, the Product Operations team is an integral part of delivering great products to the world. Product Operations is the connective tissue between Research, Product, and the market. We shorten the distance between what our models can do and what people get to use. Each of us sits inside one product team as an extension of its leadership, and together we run one shared operating system for how Anthropic ships and learns. On a given day you might get a launch through its final review, run an early access window, or triaging customer feedback. The rest of the week you build the systems so the team ships and learns faster next time. Our team is small and gets unusual leverage from Claude enabling us to fill gaps across the company and deliver outsized value. Responsibilities: 1. Ship with confidence Own launch readiness for your team. Keep our launch calendar the source of truth for what is shipping and when. Get every major launch through go/no-go: pre-read written, Security, Safeguards, Legal, and Commercial sign-offs recorded, and any accepted risk written down on purpose. Run early access and beta programs that return signal Product and Research can act on. Define the question before the window opens, give testers the scaffolding to answer it, and close each one with a retro on whether the feedback landed. Program manage new model launches on your surface: readiness goals set in advance, testing and eval coverage tracked, issues triaged, prompting changes landed, retro run. You won't write the evals. You run the program around them. 2. Close the loop with users Turn a lot of noise into two clear signals: what users are asking for, ranked by impact and mapped to the roadmap, and which customers or cohorts are blocked, on what, and why it matters. Plug your team into Anthropic's shared feedback systems rather than building a private one, and improve the shared systems where they fall short. Make sure the field, Support, and Research hear back about what happened with what they sent. 3. Run the team's operating system Set the team's pace: planning, business and execution reviews, goal tracking, offsites. Own how your team works with Legal, Safeguards, Security, GTM, and other product teams so partnering with your team is predictable. Push reporting overhead toward zero. Reviews and digests should be generated from data that already exists. Fill the gaps. Every embedded seat carries one or two projects unique to its team, for example managing Monthly Business Reviews and helping track progress between cycles. 4. Build with Claude Build the tools you need yourself: Claude-powered triage, dashboards that read and write to our systems of record, skills and agents that take the chasing out of the job. Contribute what you build back to the ProdOps team as reusable patterns (launch checklists, EAP setup, lookbacks, deprecations) so nobody starts from scratch. You may be a good fit if you have: Have owned an operational program end to end (launches, early access, feedback, or planning) that a product team relied on to make decisions. You designed it and ran it, not just executed someone else's plan. Have built a process from zero to one and then simplified it as it scaled. You treat process as a product: it has users, metrics, and a happy path people want to follow. Have worked embedded with product leadership and can move a team without formal authority. Build with AI yourself. You have shipped Claude or other LLM-powered workflows, written the prompts, iterated on the outputs, and can describe model behavior with specifics. Have direct experience managing evals, refining system prompts, and adapting harnesses to new models. Have direct experience working with Cloud providers in partnership or GTM capacity Have commitment to safe deployment of AI. Bonus if experience with AI Safety and Safeguards. Bonus: Program managed model launches or model quality at an application-layer AI product. Run early access, beta, or design partner programs. Product management, technical program management, chief of staff, or strategy and operations experience at a startup or fast-growing product company. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $260,000 — $325,000 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: San Francisco, CA 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 business metrics change quickly. New models, products and pricing land every few weeks, and each one moves the numbers in ways leadership needs to understand and act on quickly. The Finance Analytics & Business Intelligence team is hiring a senior individual contributor to own how finance leadership reviews key business metrics. You'll run the weekly company metrics update and forum, explain what is driving revenue and usage across products, customers and models, and turn open-ended business questions into clear, data-driven answers. You'll also build what makes those answers repeatable and scalable: governed metric definitions, executive dashboards, and Claude-powered workflows for recurring analysis. The work is technical, fast-moving and highly visible, and it spans Finance, Product, Go-to-Market, Data Science and Data Engineering. In this role, you will: Own the weekly company metrics update and forum: shape the story the numbers tell, evolve the structure and content as fast as the business changes Define the metrics that matter: help establish the headline KPIs leadership uses to track the business, and the driver views beneath them. Surface macro trends: explain what is driving growth across products, customers, and channels, and flag leading indicators early Lead deep dives on executive questions: take a broad question from leadership, put a measurement approach around it, and work with partner teams to deliver a clear, defensible answer Track performance against plan: explain where actuals differ from forecast and why it matters Partner across teams: work with finance leadership, product and GTM finance and strategy, data science, and data engineering to agree on how we measure the business, so everyone uses the same numbers. Raise the bar: land narratives in executive forums and up-level the team’s finance analytics practice by example You might be a good fit if you: Have run an executive metrics forum: you've owned a recurring business review for senior leadership, including its structure, content and discussion. Land narratives with executives: your analyses have changed business decisions, and you can simplify for senior leaders without losing rigor Put shape around ambiguity: you’ve personally defined the measurement approach for questions nobody knew how to answer, without waiting for a fully specified ask Stay hands-on at senior scope: you still write the SQL and Python yourself, and you’d rather ship a defensible v1 with honest error bars than wait for perfect data Are inherently curious: you go one level deeper than asked and are energized by how fast models, products, and the market are moving Thrive amid shifting priorities: you juggle multiple fast-moving work streams and stay effective when the plan changes weekly Work fluently with modern tooling: you’re strong at data visualization, use Claude and AI tools as force multipliers in analysis and BI, and can self-serve your own workflows across SQL, Python, dbt, and a cloud warehouse Strong candidates may also have: Significant experience in finance analytics, business analytics or data science, including direct partnership with senior leadership Revenue or growth analytics experience at a usage-based business (cloud, API or marketplace) Ownership of a company or executive business review Experience designing evals or benchmarks for AI models or products Fluency in the LLM model and product landscape Experience with a semantic or metrics layer Dimensional modeling and warehouse design experience (grain, SCDs, point-in-time correctness) Cloud platform experience (AWS, GCP) with orchestration, CI/CD for data, and testing/observability The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $270,000 — $345,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: New York City, NY; San Francisco, CA 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 Scaled Enterprise team is a high-velocity sales motion built to bring frontier AI to a broad set of enterprise accounts. We're focused on reaching new customers efficiently, turning first conversations into real, expanding partnerships, and building the playbook for how Anthropic shows up at scale. As a Scaled Enterprise Account Executive, you'll own a book of enterprise accounts and the full revenue outcome for each. You'll generate your own pipeline, run a high-velocity sales cycle from first conversation through close, and develop a clear point of view on where Claude creates value in each account. You'll work closely with Product, Applied AI, and GTM to learn what's working at scale and feed it back into the playbook we're building from the ground up. This is a role for someone who thrives in hypergrowth, gets energy from breaking into new enterprise accounts, and wants to help build the scaled motion at Anthropic — not inherit one. Responsibilities Own all revenue outcomes for a book of enterprise accounts, driving new logo acquisition and early expansion across multiple use cases Generate the majority of your own pipeline through outbound, creative prospecting, and proactive multithreading into enterprise accounts that have not yet engaged with Anthropic Run a high-velocity sales cycle from first meeting through close, qualifying quickly, advancing rigorously, and knowing when to walk Develop a clear point of view on where Claude creates value in each account and bring that POV to technical and business stakeholders alike Build relationships with directors, VPs, and executive sponsors within your enterprise accounts, earning the right to expand by delivering early wins Negotiate and close commercial agreements involving technical evaluations, security review, and enterprise procurement Partner with Product, Applied AI, and Engineering to surface what's working, what's not, and what enterprise buyers need next Contribute to the playbook, proof points, and motion that this team is building from the ground up You may be a good fit if you have 3-5+ years selling into enterprise accounts as a full-cycle individual contributor carrying a bag, with a track record of consistently exceeding quota Experience selling at a hypergrowth company, where the playbook was still being written and you helped write it A hunter mindset and demonstrated success generating your own enterprise pipeline and breaking into new enterprise accounts Experience running enterprise sales cycles involving technical evaluations, security review, and procurement Comfort engaging both technical and business buyers at the director and VP level within enterprise organizations Background selling platform, API, cloud infrastructure, developer tools, or AI/ML into enterprise Strong commercial instincts and the ability to qualify quickly and advance rigorously Genuine interest in AI and strong alignment with Anthropic's mission of developing AI systems that are safe and beneficial What will make you stand out Experience at a hypergrowth enterprise infrastructure or developer tools company in its scaling years Track record as one of the early AEs on a new team, segment, or product where you helped build the motion rather than inherit it Background in developer tools, API, or AI/ML sales into technical buyers The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $290,000 — $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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: London, UK; Ontario, CAN; Remote-Friendly, United States; San Francisco, CA 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. Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. Apply at the bottom of this page. We are accepting applications on a rolling basis for the next cohort expected to start in January 2027. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the January 2027 start date doesn't work for you. What to expect 4 months of full-time research Direct mentorship from Anthropic researchers Access to a shared workspace Connection to the broader AI safety and security research community Weekly stipend of 4,615 USD / 3,440 GBP / 6,470 CAD / 4,110 EUR + benefits (these vary by country) Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application, assessments, and interviews. We may ask for references later in the process as well. 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. Compensation The expected base stipend for this role is 4,615 USD / 3,440 GBP / 6,470 CAD / 4,110 EUR per week, with an expectation of 40 hours per week for 4 months (with possible extension). ML Systems & Performance Fellows Mentors, research areas, & past projects Fellows will undergo a project selection & mentor matching process. Potential mentors include: Alwin Peng Zygi Straznickas Note: You may research mentors' prior work, but all applications must go through the official form, not the mentors. For a past example of an engineering-heavy project, see: AI agents find $4.6M in blockchain smart contract exploits Projects in this workstream may include: Building a CPU simulator for accelerator workloads Adding backends for different accelerators on an open source project Building on demand infrastructure for other infrastructure heavy fellows projects Building complex synthetic data or environment pipelines Unique candidate criteria You might be a particularly great fit for this workstream if you: Have strong software engineering skills with experience building complex ML systems Can balance research exploration with engineering rigor and operational reliability Enjoy collaborating across research and engineering disciplines Are comfortable working with large-scale distributed systems and high-performance computing (e.g. in trading) Have experience with training, fine-tuning, or evaluating large language models Are adept at analyzing and debugging model training processes You may be a good fit if you Are motivated by making sure AI is safe and beneficial for society as a whole Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic Have a strong technical background in computer science, mathematics, or physics Thrive in fast-paced, collaborative environments Can implement ideas quickly and communicate clearly Candidates must be Fluent in Python programming Available to work full-time on the Fellows program Reinforcement Learning Fellows Mentors, research areas, & past projects Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include: Ruhua Jiang Kaidi Cao Sunny Duan David Brandfonbrener Colt Steele Dino Distefano Will Williams Projects in this workstream may include: Building model-based tools to better understand AI training data and improve training data quality A research project to better understand generalization Creating RL environments to improve Claude models at capabilities that are within your domain of expertise Building RL environments for safety-related tasks Conducting research and implementing solutions in areas such as RL algorithms Unique candidate criteria You might be a particularly great fit for this workstream if you: Have strong software engineering skills with experience building complex ML systems Can balance research exploration with engineering rigor and operational reliability Enjoy collaborating across research and engineering disciplines Are comfortable working with large-scale distributed systems and high-performance computing Have experience with training, fine-tuning, or evaluating large language models Are adept at analyzing and debugging model training processes Logistics Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program. Workspace Locations: We have designated shared workspaces in SF. We are also open to remote fellows in the UK, US, or Canada . Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada. Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis. Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations. The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program. 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: London, UK; Ontario, CAN; Remote-Friendly, United States; San Francisco, CA 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. Applications are now open for our January cohort - apply here by October 30. Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. What to expect 4 months of full-time research Direct mentorship from Anthropic researchers Access to a shared workspace (in either Bay Area, California, Toronto, Canada, or London, UK) Connection to the broader AI safety and security research community Weekly stipend of 4,615 USD / 3,440 GBP / 6,470 CAD / 4,110 EUR + benefits (these vary by country) Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. 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. Compensation The expected base stipend for this role is 4,615 USD / 3,440 GBP / 6,470 CAD / 4,110 EUR per week, with an expectation of 40 hours per week for 4 months (with possible extension). Across the workstreams, you may be a good fit if you: Are motivated by making sure AI is safe and beneficial for society as a whole Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic Have a strong technical background in computer science, mathematics, or physics Thrive in fast-paced, collaborative environments Can implement ideas quickly and communicate clearly Strong candidates may also have: Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity) Experience in areas of research or engineering related to their workstream Candidates must be: Fluent in Python programming Available to work full-time on the Fellows program AI Safety Fellows Mentors, research areas, & past projects Fellows will undergo a project selection & mentor matching process. Potential mentors include: Sam Bowman Sara Price Alex Tamkin Nina Panickssery Trenton Bricken Logan Graham Jascha Sohl-Dickstein Joe Benton Collin Burns Fabien Roger Samuel Marks Kyle Fish Ethan Perez Our mentors will lead projects in select AI safety research areas, such as: Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains. Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Model Internals / Mechanistic Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures. AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations. On our Alignment Science and Frontier Red Team blogs, you can read about past projects, including: Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data: Alex Cloud and Minh Le, et al., mentors including Samuel Marks and Owain Evans Open-source circuits: Michael Hanna and Mateusz Piotrowski with mentorship from Emmanuel Ameisen and Jack Lindsey For a full list of representative projects for each area, please see these blog posts: Introducing the Anthropic Fellows Program for AI Safety Research , Recommendations for Technical AI Safety Research Directions . Unique candidate criteria You might be a particularly great fit for this workstream if you: Are motivated by reducing catastrophic risks from advanced AI systems Have experience with empirical ML research projects Have experience working with large language models Have experience in one of the research areas mentioned above Have a track record of open-source contributions AI Security Fellows Mentors, research areas, & past projects Fellows will undergo a project selection & mentor matching process. Potential mentors include: Nicholas Carlini Keri Warr Evyatar Ben Asher Keane Lucas Newton Cheng On our Alignment Science and Frontier Red Team blogs, you can read about some past Fellows projects, including: AI agents find $4.6M in blockchain smart contract exploits: Winnie Xiao and Cole Killian, mentored by Nicholas Carlini and Alwin Peng Strengthening Red Teams: A Modular Scaffold for Control Evaluations: Chloe Loughridge et al., mentored by Jon Kutasov and Joe Benton Unique candidate criteria You might be a particularly great fit for this workstream if you: Are motivated by reducing catastrophic risks from advanced AI systems Have contributed to open-source projects in LLM- or security-adjacent repositories Have demonstrated success in bringing clarity and ownership to ambiguous technical problems Have experience with pentesting, vulnerability research, or other offensive security work Have a demonstrated willingness to do the "dirty work" that produces high-quality outputs Have reported CVEs or been awarded bug bounties Have experience with empirical ML research projects Have experience with deep learning frameworks and experiment management Logistics Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program. Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada . We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program. Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada. Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis. Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations. Applications and interviews are managed by Constellation , our recruiting and program partner. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities-focused projects in future rounds. Apply here by October 30. The below are Anthropic's policies for full-time roles. These do NOT apply to the Fellows Program. 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: New York City, NY; San Francisco, CA 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 GSI team partners with the world’s largest Global System Integrators and strategy consultancies to deploy frontier AI into the core of how they deliver client work and run their own businesses. These are complex, partner-led organizations where the first engagement is rarely the full opportunity, and where lasting partnerships are built across practice areas and at the executive level. As an Strategic Account Executive on the GSI team, you’ll own a named book of accounts and the full revenue outcome for each. You’ll develop a point of view on where Claude creates the most value across a firm’s practice areas, advisory services, delivery teams, and internal operations, build relationships with the partners and executives who sponsor transformation at that scale, and expand the partnership well beyond the original buyer. These firms are both customer and future channel — your sell-to motion sets up the sell-with later. You’ll work closely with Product, Applied AI, GTM, and Partnerships leadership to shape how Anthropic shows up across the GSI landscape, while advancing our mission of developing AI that is safe, beneficial, and deployed responsibly. This is a role for someone who has owned large, complex partner-led accounts end to end and is comfortable operating independently at the executive level. Responsibilities Own all revenue outcomes for a named book of GSI accounts, driving both new logo acquisition and multi-practice expansion through complex, multi-quarter sales cycles involving partner-led approval, global procurement, and custom commercial terms Develop a clear thesis for each priority firm — where Claude creates value across knowledge management, advisory workflows, deliverable generation, and client engagements — and execute a sequenced engagement plan across practices, regions, and stakeholders Build and independently advance executive relationships with Managing Partners, Practice Leads, MDs, CIOs, CTOs, and Heads of AI/Digital, anchoring every conversation to their strategic priorities: utilization, leverage, realization, and billable productivity Proactively create demand in unengaged practice areas and regions, using early wins as proof points to open new doors across decentralized, partner-led organizations Build quantified, firm-specific business cases mapped to the GSI operating model — using their own language and metrics — that shape deals rather than justify them after the fact Identify and close lighthouse partnerships that become references across the GSI landscape and set up the future sell-with motion Partner cross-functionally with Product, Applied AI, Engineering, and Partnerships to inform the roadmap based on GSI buyer needs, and contribute to the playbook, proof points, and commercial structures that become the repeatable GSI motion You may be a good fit if you have 8+ years of enterprise software sales experience with a track record of owning named accounts at large, complex, partner-led organizations (global SIs, strategy consultancies), managing multi-quarter sales cycles through technical evaluations, partner-led approval, and global procurement Demonstrated ability to independently build and advance relationships at the Partner, MD, and C-suite level — including practice leadership and innovation/digital executives — and hold credible conversations across both technical and business audience Experience building firm-specific business cases grounded in the firm's own operating metrics (utilization, leverage, realization, margin) and defending commercial terms through complex negotiations Background selling platform, API, cloud infrastructure, or emerging technology into enterprises evaluating a new category Genuine interest in AI and strong alignment with Anthropic's mission of responsible AI development A history of growing accounts meaningfully beyond the original engagement by proactively creating demand across new practice areas, regions, and use cases What will make you stand out Direct experience selling into Global SI’s or strategy consultancies, and fluency in how partner-led firms operate and measure success Experience as an early AE in a vertical or segment, where you helped build the sales motion rather than inherit it Background selling developer platforms, cloud infrastructure, or AI/ML tooling into traditional partner-led services firms The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $380,000 — $450,000 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Product Engineering org is looking for experienced engineers with strong full-stack fundamentals to join one of teams owning our current or emergent products. You'll be a technical leader who thinks holistically about the consumer and/or enterprise end user experience - be that via Claude.ai , the Anthropic API, enterprise deployments, Claude Code, or mission-driven applications - and carry real end-to-end ownership. You'll partner with engineering managers, product leaders, designers, and researchers to understand new model capabilities and redefine what is possible for users in the world of LLMs - and how to build it. We’ll look to you to have a product-oriented mindset and input, own technical quality across the stack (performance, accessibility, reliability, and developer experience), scale your efforts to millions of users on a global scale, and carry genuine excitement about what AI makes possible. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. What you'll do: Developer Experience: You'll build the products and tools - console, SDKs, docs, and observability - that give developers the confidence to rely on Claude in their most critical applications. Our mission is to meet developers where they are and bring them closer to the ceiling of what's possible with our models and API. That means building trust through great platform fundamentals, inspiring developers to raise the bar in how they use Claude's capabilities, and accelerating the path to agentic development by designing for both human and AI developers. You'll work closely with teams across the Platform org to turn Claude's newest capabilities into experiences developers can actually pick up and run with - from first prompt to production agent. Beneficial Deployments: Beneficial Deployments Engineering brings Claude to organizations doing the most good with the fewest resources — nonprofits, schools, healthcare providers, researchers, and economic mobility programs.We're looking for a full-stack engineer to build the access programs, tooling, and product work that make frontier AI usable for teams that couldn't afford this capacity any other way. Vertical AI Products: Purpose-built experiences for specific industries where Claude can transform complex professional work. We're currently building for three verticals, with more to come: Life Sciences — an agentic research platform for scientists: specialist agents for computational biology, literature review, and regulatory review, built on model capabilities we're investing in for biology and chemistry. Live with early customers and expanding fast. Enterprise AI Products: You'll work on the products that make Claude a daily-use tool for enterprise customers across industries – the connective tissue that lets Claude operate effectively across workflows. On this team you will systematically understand why Enterprise users aren't activating, what's blocking adoption, and building the capabilities to close those gaps.Some of our focuses are: Extensibility — plugins, skills, connectors, and the MCP ecosystem that lets a company shape Claude around their specific workflows and distribute that work across teams. Context — enterprise knowledge, organizational memory, and the retrieval layer that makes Claude genuinely aware of a company's people, documents, and workflows. A connected, contextual Claude is the difference between a general-purpose chatbot and a real coworker. Proactivity — Cowork suggestions, workflow capture, ambient Claude inside the apps people already use. Moving from "Claude answers when asked" to "Claude notices what you need". Public Sector: Build products that deliver Claude to the U.S. federal & state governments and allied democracies — from FedRAMP environments to classified networks. We're a startup-minded team with huge surface area: we own Claude for Government, ship zero-to-one products into the most regulated environments in the world, and work directly with the agencies using them. Enterprise Foundations: You'll build the systems large organizations require before they can adopt Claude at scale: identity and permissions, security and compliance controls, and the admin analytics that let them see how it's being used. This is the work that turns "we love the demo" into a signed enterprise deal.The role is part product, part platform. You'll work closely with Product and GTM to understand what our largest customers need, then build it once in a way that works across Claude.ai, Claude Code, and Cowork. Growth: Drive user acquisition, engagement, retention, and monetization through data-driven strategies and technical implementations. At Anthropic, we're not just building AI tools; we're reimagining how AI can enhance and expand its user base! As a member of the growth team, you will have a unique opportunity to shape our growth strategy. You will work with a cross-functional team of engineers, data scientists, marketers, and product managers to design, implement, and optimize growth initiatives that scale our AI-powered tools and maximize their impact. You might be a good fit if you: Have a minimum of 6 years of practical full-stack engineering experience Have led the design and delivery of complex, consumer or B2B user-facing products across the full stack Are technically proficient in modern frontend and backend development, with demonstrated depth in key languages and frameworks (ie. React, Typescript) Take a product-focused approach to building solutions that are robust, scalable, and easy to use Have worked in early start-up or otherwise fast moving, rapidly evolving environments, and have ideally built products from 0 to 1 Have successfully driven cross-team alignment to get impactful work shipped, and work with influence over authority Have experience establishing engineering standards, component architectures, and development best practices Thrive in fast-paced environments and can navigate ambiguity to deliver high-quality products Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of teams. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Product Engineering org is looking for experienced engineers with strong full-stack fundamentals to join one of teams owning our current or emergent products. You'll be a technical leader who thinks holistically about the consumer and/or enterprise end user experience - be that via Claude.ai , the Anthropic API, enterprise deployments, Claude Code, or mission-driven applications - and carry real end-to-end ownership. You'll partner with engineering managers, product leaders, designers, and researchers to understand new model capabilities and redefine what is possible for users in the world of LLMs - and how to build it. We’ll look to you to have a product-oriented mindset and input, own technical quality across the stack (performance, accessibility, reliability, and developer experience), scale your efforts to millions of users on a global scale, and carry genuine excitement about what AI makes possible. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. What you'll do: Platform Ecosystem: The Ecosystem team is empowering the next big industries beyond coding to build on our platform & creating the right commercial rails to let any business in our ecosystem profit from building on Claude. As an early member of this foundational effort, you'd identify and build for the next 10x markets starting with Life Sciences and Healthcare. We also build the commercial rails and controls that let the platform do business anywhere, with anyone, and turn Claude from a cost line into a revenue line. Beneficial Deployments: Beneficial Deployments Engineering brings Claude to organizations doing the most good with the fewest resources — nonprofits, schools, healthcare providers, researchers, and economic mobility programs.We're looking for a full-stack engineer to build the access programs, tooling, and product work that make frontier AI usable for teams that couldn't afford this capacity any other way. Vertical AI Products: Purpose-built experiences for specific industries where Claude can transform complex professional work. We're currently building for three verticals, with more to come: Life Sciences — an agentic research platform for scientists: specialist agents for computational biology, literature review, and regulatory review, built on model capabilities we're investing in for biology and chemistry. Live with early customers and expanding fast. Enterprise AI Products: You'll work on the products that make Claude a daily-use tool for enterprise customers across industries – the connective tissue that lets Claude operate effectively across workflows. On this team you will systematically understand why Enterprise users aren't activating, what's blocking adoption, and building the capabilities to close those gaps.Some of our focuses are: Extensibility — plugins, skills, connectors, and the MCP ecosystem that lets a company shape Claude around their specific workflows and distribute that work across teams. Context — enterprise knowledge, organizational memory, and the retrieval layer that makes Claude genuinely aware of a company's people, documents, and workflows. A connected, contextual Claude is the difference between a general-purpose chatbot and a real coworker. Proactivity — Cowork suggestions, workflow capture, ambient Claude inside the apps people already use. Moving from "Claude answers when asked" to "Claude notices what you need". Public Sector: Build products that deliver Claude to the U.S. federal & state governments and allied democracies — from FedRAMP environments to classified networks. We're a startup-minded team with huge surface area: we own Claude for Government, ship zero-to-one products into the most regulated environments in the world, and work directly with the agencies using them Enterprise Foundations: You'll build the systems large organizations require before they can adopt Claude at scale: identity and permissions, security and compliance controls, and the admin analytics that let them see how it's being used. This is the work that turns "we love the demo" into a signed enterprise deal.The role is part product, part platform. You'll work closely with Product and GTM to understand what our largest customers need, then build it once in a way that works across Claude.ai, Claude Code, and Cowork. Growth: Drive user acquisition, engagement, retention, and monetization through data-driven strategies and technical implementations. At Anthropic, we're not just building AI tools; we're reimagining how AI can enhance and expand its user base! As a member of the growth team, you will have a unique opportunity to shape our growth strategy. You will work with a cross-functional team of engineers, data scientists, marketers, and product managers to design, implement, and optimize growth initiatives that scale our AI-powered tools and maximize their impact. You might be a good fit if you: Have a minimum of 8 years of practical full-stack engineering experience, ideally with 2+ years operating at a Staff or equivalent technical leadership level Have led the design and delivery of complex, consumer or B2B user-facing products across the full stack Are a technical expert in modern frontend and backend development, with demonstrated depth in key languages and frameworks (ie. React, Typescript) Take a product-focused approach to building solutions that are robust, scalable, and easy to use Have worked in early start-up or otherwise fast moving, rapidly evolving environments, and have ideally built products from 0 to 1 Care deeply in investing in the mentorship and growth of your peers Have successfully driven cross-team/cross-org organizational alignment to get impactful work shipped, and work with influence over authority Have experience establishing engineering standards, component architectures, and development best practices Thrive in fast-paced environments and can navigate ambiguity to deliver high-quality products Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, NJ, SEA, SF or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic is looking for experienced, product-minded engineers to own the backend systems that power user experiences across our API, Claude Code, and Claude.ai. You'll independently scope complex, multi-month projects through ambiguous problem spaces and lead peers through technical and product decisions; you'll drive alignment with product, peer engineering teams, and research to identify capability gaps and translate frontier model improvements into shipped products. You'll make architectural decisions that affect the reliability and scalability of systems serving hundreds of thousands of global users (including internal teams), and design processes that help your team operate effectively and never fail the same way twice - all while staying hands-on with the code and our models. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential: Platform Intelligence: You'll build and scale the foundation of the Claude API—the systems that deliver Claude's intelligence to every developer, from startups to enterprise. You'll own the performance, reliability, and efficiency of our core serving path, ensuring users get the most speed and value from our models. You'll partner closely with inference and safeguards to optimize the full stack. Platform Ecosystem: The Ecosystem team is empowering the next big industries beyond coding to build on our platform & creating the right commercial rails to let any business in our ecosystem profit from building on Claude. As an early member of this foundational effort, you'd identify and build for the next 10x markets starting with Life Sciences and Healthcare. We also build the commercial rails and controls that let the platform do business anywhere, with anyone, and turn Claude from a cost line into a revenue line. We are hiring founding engineers for these two pillars. We are looking for engineers who have good product and business sense to drive strategy, dive into different stacks, and break through walls to drive these 0 -> 1 efforts. You'll be working closely with product, design, GTM, FDE, and other internal & external customers to build out and deliver on the strategy. Platform Serving: You'll focus on transforming Claude into a true knowledge worker by ensuring the model has access to and understanding of the right knowledge at the right time. You'll work on making it possible for developers to securely give Claude access to their data while automatically processing and retrieving relevant information. You'll partner directly with research to bring state-of-the-art retrieval advancements to developers. Developer Experience: You’ll focus on building products and tools to enable developers to harness the full power of LLMs to create successful, reliable, and groundbreaking applications with ease. You’ll build the tools to accelerate developers from idea to deployment. You'll help figure out how to leverage Claude to improve developer's usage of the API, such as generating and evaluating prompts while collaborating closely with the teams above to bring Claude's current and future capabilities to developers. Agentic Systems: You'll build the infrastructure and APIs that let developers create powerful agentic applications on the Claude API — including Claude Managed Agents, our managed platform for deploying and running agents in production. Your work spans the primitives agent developers depend on: tool use, multi-step reasoning, durable sessions and environments, and long-running task execution that lets Claude take actions and accomplish complex goals on a user's behalf. You'll make this platform ready for the largest enterprises to adopt, and partner with research to bring cutting-edge agent capabilities into production. Auth & Identity: We build and maintain the critical infrastructure and control interfaces that power identity and authentication across Anthropic's product suite. We work closely with product teams, security, support, and trust & safety as customers. We create scalable solutions for user authentication, authorization, role-based access control, and single sign-on that form the backbone of our company's identity management operations. We maintain a user-centric approach, building reliable systems that our users and company can depend on as we tackle complex challenges at the intersection of security, scalability, and user experience. Platform Distribution: The Claude API today is a rapidly growing platform serving developers and enterprises at scale—but reaching the next tier of enterprise customers requires transforming how and where we deploy it. The Distributability team owns that transformation: making the Claude API a cloud-native, managed product that runs wherever our customers need it, cross-cloud and on Anthropic's own infrastructure, with the enterprise-grade security, compliance, and operational capabilities to support it. Enterprise Foundations: We're looking for a software engineer to join our Enterprise Foundations team—the team that makes Claude enterprise-ready at scale. When a Fortune 500 company wants to roll out Claude to 100,000 employees, we're the team that makes it possible.You'll build the foundational systems that large organizations require before they can deploy AI at scale: user and permissions management, security and compliance features, and analytics infrastructure. This work directly converts product-market fit into revenue by removing the deployment blockers that prevent large organizations from adopting Claude broadly. Platform Safety: We're building the identity and verification product layer that enables safe model launches as Claude's capabilities expand. This critical effort partners with Safeguards, Auth & Identity, Policy, and Product teams across API, Claude.ai , and third-party platforms as customers, creating the systems for KYC/KYB, trust grant issuance and inheritance, and end-user verification that flow across every Anthropic surface. We sit at the intersection of trust, compliance, and product velocity, delivering the verification primitives that let Anthropic ship advanced model capabilities to the right users at massive scale. You Might Be a Good Fit If You: Have 8+ years of relevant experience as a backend or product engineer, with a track record of leading complex, multi-month projects or teams as a tech lead or equivalent Have strong coding fundamentals and are comfortable working across backend systems, APIs, and integrations — and can reach into the frontend when needed to ship an effective solution Have led the design and delivery of large-scale backend systems in production that power high-adoption B2B or consumer facing products Are skilled at driving alignment across technical and non-technical teams; you communicate clearly, influence technical decisions beyond your immediate team, and help others ramp effectively on your systems Take a product-focused approach to your work work and care about building solutions that are robust, scalable, and easy to use Care deeply about investing in the mentorship and growth of your peers Have experience with distributed systems, API design, and cloud infrastructure at scale Thrive in fast-paced environments and can navigate ambiguity to find the highest-leverage path forward 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: We are looking for experienced software engineers to join our Platform organization. We build the foundational primitives that accelerate product development across Anthropic, and own infrastructure and systems that teams depend on to ship reliably and at scale - either internally or by hundreds of thousands of external global users and companies at all stages. You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You'll partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. You might be a good fit if you: Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent distributed systems, cloud-native products, developer tools, or external developer facing products Have strong fundamentals in service-oriented architectures, networking, and systems design, ideally having owned both the technical vision and execution of a foundational platform system end to end Are proficient in Python, Go, Rust, or similar systems languages Have experience with cloud infrastructure (GCP, AWS, or Azure), container orchestration (Kubernetes), and/or multi-cloud networking Take full ownership of your work—from design through deployment and operations Can navigate ambiguity and make sound technical decisions independently, and have ideally operated in 0 to 1 and more mature team or company settings Take a product-focused approach to platform work and care about building solutions that are robust, scalable, and easy to use Care about building systems that other engineers love to use Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: Switzerland Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. - Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. Location & Employment - Location: remote within Switzerland - Employment type: Full-time, permanent employment - Hiring model: Employment via Employer of Record (EOR) Candidates must already have the legal right to work in Switzerland, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: UK Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. The base salary range for this full-time position is £140,000 – £200,000. In addition to base pay, total compensation includes equity and benefits. Within the range, individual pay is determined by work location, level, and additional factors, including competencies, experience, and business needs. The base pay range is subject to change and may be modified in the future. Candidates must already have the legal right to work in the United Kingdom, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Serbia Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. - Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Germany Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. - Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Mountain View, California, USA Workplace: Hybrid About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. We believe in the power of in-person collaboration to solve the hardest problems and foster a strong team culture. We offer relocation assistance and look forward to you joining us in our Mountain View office. The base salary range for this full-time position is $270,000 - $430,000+ bonus + equity + benefits. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: San Francisco Bay Area About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. About the Role We’re hiring a Director of Finance to own the financial backbone of HumanSignal, the company behind Label Studio. Reporting directly to the CEO, you’ll own financial planning, business analytics, and the metrics infrastructure that drives decision-making across the company,  including our SaaS & labeling services business. This is a hands-on leadership role with broad scope. You’ll partner with the executive team on strategy and planning, work cross-functionally with product, marketing, and sales, and build the financial infrastructure we need for the next stage of growth. If you’re energized by ownership, building from scratch, and operating at the intersection of strategy and execution, this is your role. What You’ll Own Financial Planning & Analysis Own the full P&L and free cash flow forecast; build and maintain our long-range financial model Lead the annual and quarterly planning cycle, including budgets, variance analysis, and ad-hoc modeling Deliver weekly KPI reporting to the executive team and board/investor reporting packages Revenue & Deal Operations Run deal desk operations in partnership with Sales and Customer Success to ensure coherent deal structure and pricing Build and manage sales commission and incentive plans Develop, align, and drive accountability around company-wide KPIs Labeling Services Metrics & Economics Own the financial model for our labeling services business, including project-level profitability, utilization, and margin analysis Partner with services leadership to develop pricing models, capacity planning, and resource forecasting Track and report on services revenue, backlog, and pipeline as a distinct business line alongside software ARR Board & Strategic Support Own end-to-end board meeting preparation, including deck creation, data packages, and follow-ups Partner with leadership on strategic initiatives, business cases, and scenario planning Serve as primary liaison to external accounting, tax, and payroll services What You’ll Bring 5+ years in an FP&A, finance, or business analytics role at a high-growth startup, or relevant experience in management consulting Experience building financial infrastructure largely from scratch, you’re comfortable being the first dedicated finance hire Strong command of SaaS metrics: ARR, NDR, CAC payback, gross margin Experience with services or professional services financial modeling (utilization, project margins, blended rates) is a strong plus Highly analytical with advanced modeling skills Experience preparing board materials, investor updates, and executive-level reporting Ability to build a case and tell a persuasive story that drives decision-making across the organization Self-starter who can own complex projects end-to-end with minimal direction Startup mentality, no job is too small, and you default to action over analysis You’re familiar and utilizing all of the latest AI tooling and support to make yourself more efficient Attention to detail. In your application, tell us about a financial model you built that turned out to be wrong, and what it taught you. We read every application and want to make sure you do the same. What Success Looks Like First 30 Days Own the financial model, take over the P&L and FCF forecast and identify gaps or errors Deliver your first board data package with minimal hand-holding Produce an initial labeling services P&L with project-level margin visibility Audit external accounting and payroll vendors; present a recommendation on any changes First 90 Days Own the full board prep process end-to-end, including the deck, data, and follow-ups Ship a company-wide KPI framework with named owners, targets, and a weekly reporting cadence Work alongside product to create pricing structure for new product / add-ons Deliver a revised deal desk process with documented pricing guardrails and approval workflows First 6 Months Rebuild the long-range financial model to support scenario planning across software and services Execute at least two pricing or cost optimization initiative with measurable impact Be the person leadership relies on for any financial question, no one should need to go elsewhere

Location: New York City, NY 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 Join Anthropic's Customer Success team in a high-impact role driving AI adoption across our Industry segment. As an Enterprise Customer Success Manager for Industries, you'll be the strategic partner and a trusted advisor to our most complex customers with a portfolio spanning Entertainment, Insurance, Manufacturing and Retail organizations—helping them harness the full potential of all our Claude capabilities - API, Claude for Enterprise, and Claude Code. You'll work with organizations across diverse industries that are transforming their businesses with AI technology. Developing genuine partnerships with customers, gaining a deep understanding of their business objectives, strategic direction, AI vision, and technical needs. You'll draw on both your business acumen and technical expertise to serve as a strategic advisor throughout their journey with us. In partnership with the broader account team you will help customers identify the right Claude capabilities for their specific business objectives, working closely with them to provide best practices and guidance while supporting them as their usage (consumption & seat based) grows and evolves. Your role focuses on helping customers scale their usage effectively, drive model and use case optimizations, implement change management strategies, and maximize the value of their investment through expanded use cases across their organization. The insights you gather from your customers will directly inform our research priorities, product development, and go-to-market strategies — making you a key voice in shaping how we build and deliver ongoing value as a business. Responsibilities: Build trusting, strategic relationships with key customer decision makers to understand their business and objectives, identifying opportunities for optimization and expansion Become an expert in Anthropic's products across API, Claude Code and Claude for Enterprise, understanding the technical nuances and best practices for each to guide customers to the right solutions Leverage your deep knowledge of the customer and their industry vertical to proactively drive usage planning, understanding current and future consumption/adoption and how it creates realized value for the customer Monitor usage patterns and identify optimization opportunities, proactively addressing underutilization across both consumption-based (API) and seat-based (Claude for Enterprise / Claude Code) products to drive full value from contracted commitments Serve as the customer's thought partner, enhancing their knowledge of Claude products by socializing Anthropic's product roadmap, driving awareness on new products and engaging Product PMs Document and quantify customer value realized through business outcomes, ROI, and impact metrics to build compelling internal business cases for continued and expanded investment Identify potential use cases and lines of business not currently onboarded, partnering with customers and Sales to discover new applications for Claude across different departments, teams, and workflows Develop and execute change management strategies to drive end-user adoption and maximize value within customer organizations, including Train the Trainer programs, Center of Excellence development, and organizational enablement Own the customer experience across their lifecycle — managing comprehensive account and success plans grounded in the customer's business objectives, conducting Quarterly Business Reviews, and serving as the primary conduit between the customer and Anthropic Develop scalable engagement strategies and playbooks for your Industry portfolio, balancing high-touch strategic accounts with efficient coverage models to maximize impact across all customers You may be a good fit if you have: 6+ years of experience in Customer Success, Technical Account Management, or Solutions Engineering Experience working with enterprises in teleco, media, retail, industrial, business services Technical fluency with ability to understand and articulate AI/ML concepts, API integrations, and software implementation patterns across a set of diverse stakeholders—from developers and product managers to executives and end users Experience driving success across both consumption-based and seat-based business models, with understanding of different expansion levers and success metrics for each Strategic mindset to identify growth opportunities and translate them into actionable expansion plans Proven track record managing a portfolio of accounts while maintaining strong relationships and driving measurable outcomes Cross-functional collaborator who represents the customer in a positive, proactive manner, rallying everyone around paths forward that solve customer needs Passion for AI and interest in responsible development of advanced systems A knack for bringing order to chaos and an enthusiastic "roll up your sleeves" mentality—you're a true team player The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $200,000 — $265,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: San Francisco, CA 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 Partner Sales Manager for Systems Integrators at Anthropic, you'll own a portfolio of global and regional SI partners and be responsible for the revenue they drive. This role sits at the intersection of partnerships and sales — you'll build trusted relationships with senior stakeholders at firms like Accenture, Deloitte, and PwC, and align on joint go-to-market plans. Your main stakeholders will be sales leaders at Anthropic - helping them to land and expand enterprise deals where partner involvement is the difference between winning and not. This is an early-stage motion, which means the playbook is still being written. You'll have real influence over how we engage SIs, what good looks like for partner-sourced pipeline, and how we equip integrators to build durable Claude practices inside their organizations. You'll report to the Head of Partner Sales and work closely with Sales, Solutions Architecture, Customer Success, and Product to make sure our partners have what they need to close — and to deliver transformative AI solutions for their clients. Responsibilities: Work directly with Sales Leaders, Account Executives and Solutions Architects, bringing the partner into the sales cycle at the right moments and ensuring clear roles, clean handoffs, and shared accountability for outcomes Build relationships across multiple levels of the partner organization — from practice leads and delivery teams to alliance executives — and serve as their primary point of contact at Anthropic Own the commercial relationship with a portfolio of assigned SI partners, driving partner-sourced and partner-influenced revenue against defined targets Develop and execute joint go-to-market plans with each partner, including target account mapping, pipeline generation activities, and co-sell motions with Anthropic's direct sales team Collaborate with enablement and program teams to get your partners trained, certified, and equipped with the materials they need to position Claude effectively Track pipeline health, forecast partner-attached revenue, and surface blockers early so cross-functional teams can help unblock them Gather signal from partner interactions — what's landing, what's missing, where clients are pushing back — and feed it into product and go-to-market planning Contribute to the development of partner sales processes, playbooks, and best practices as the function scales You may be a good fit if you have: 7+ years of experience in partner sales, channel sales, alliances,  business development or direct sales at a technology company where partners are heavily involved A demonstrated track record of driving revenue through partners — you can point to pipeline you built, deals you influenced, and relationships that outlasted any single transaction Strong commercial instincts, including comfort structuring co-sell agreements, navigating multi-party deal dynamics, and knowing when to push and when to let the partner lead Experience operating in early-stage or high-growth environments where processes are still forming and you're expected to help build them Excellent communication and relationship-building skills across all levels, from partner practitioners to alliance executives A collaborative working style — you're energized by cross-functional work and understand that partner sales only works when Sales, Product, and Delivery are aligned Comfort with ambiguity and a willingness to create structure where it doesn't yet exist Willingness to travel to support partner relationships and joint customer engagements A genuine interest in AI and a belief that advanced AI systems should be developed safely and responsibly Strong candidates may also have: Experience working at a major Systems Integrator or global consulting firm, giving you firsthand insight into how these organizations make decisions, staff engagements, and build practices around emerging technology A background in AI, cloud platforms, developer tools, or other categories where technical enablement and differentiation are central to the partner motion Familiarity with consumption-based or API-first business models and how they shape partner economics and incentive design Experience managing partner relationships across multiple geographies A history of being an early member of a partner sales function and helping it scale The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $365,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.