AI Product Engineer Jobs at Anthropic with Visa Sponsorship
AI Product Engineer roles at Anthropic sit at the intersection of frontier model research and real-world product development. Anthropic has a consistent track record of sponsoring work visas for this function, supporting candidates through H-1B, H-1B1, and E-3 pathways as part of its technical hiring.
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Get Access To All JobsAbout 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 Verticals team builds AI products purpose-built for specific industries—financial services, life sciences, healthcare, and legal. Most of these teams are being built 0→1 right now: you'll be forming the team, defining the product, and shipping the first version in markets where no one has done this well yet. Where we're further along, products are already live with enterprise customers and growing fast. We're hiring Engineering Managers to lead the teams building Claude for Financial Services, Life Sciences, Healthcare, and Legal. You'll lead a team shipping AI into professional workflows—owning execution, working directly with customers and go-to-market, and helping shape where the broader Verticals group goes next. We're hiring for all four verticals through this posting. Team placement happens during the interview process based on your background, interests, and organizational need—if you have deep experience in one of these domains, let us know in your application.
About The Teams
Claude for Financial Services — Builds products for customers in investment banking, asset management, insurance, and corporate finance. Near-term work centers on deeply integrated experiences inside the tools these teams already use, with a roadmap expanding as we learn what's most useful. The team operates close to enterprise customers and close to research.
Claude for Life Sciences — We're building an agentic research platform for scientists—orchestrating specialist agents for computational biology, literature review, and regulatory review—on top of model capabilities we're investing in for biology and chemistry. The product is live with early customers and expanding fast; you'll lead engineering through that growth.
Claude for Healthcare — We're earlier here: standing up a team to build 0→1, focused initially on payer workflows (claims, prior authorization, utilization management, member communications), with groundwork for clinical applications over time. You'll be defining the product and the team at the same time.
Claude for Legal — Builds products for in-house legal teams and law firms—contract review and drafting, legal research, due diligence, and the document-heavy work that fills a lawyer's day. This team is forming now; you'll be one of the first leaders shaping what we build and who we build it with.
Responsibilities
- Lead and develop a team of engineers building new AI products for enterprise customers in your vertical
- Work closely with research to make the models better in your domain—shaping evals, surfacing failure modes, and feeding customer learnings back into model development
- Own engineering execution end-to-end: planning, prioritization, delivery quality, team health, and incident response
- Partner with sales and customer success on enterprise deals—understanding requirements, joining key conversations, and turning what you learn into engineering priorities
- Shape the roadmap with product and design, not just execute against it
- Drive the compliance and platform-readiness work your customers require, partnering with security and legal
- Recruit, onboard, and grow strong engineers; give direct feedback and build a healthy, high-performing team
You may be a good fit if you
- Have built AI products and have a practical understanding of what it takes to turn model capabilities into applications people actually use
- Are comfortable working with enterprise customers, working alongside sales and customer success and joining customer conversations
- Know the operational realities of building on platforms and integrations you don't control
- Are a skilled engineering manager who treats management as a craft—clear feedback, strong 1:1s, consistent investment in your team's growth
Strong candidates may also have
- Experience in working with research to improve domain specific model capabilities
- Experience with model evaluation frameworks and how evals inform product decisions
- Experience taking a product from 0→1—forming a team, finding product-market fit, and shipping the first version with limited precedent to lean on
- Deep domain knowledge in one of these verticals—investment banking, asset management, insurance, or corporate finance; drug discovery or computational biology; clinical operations, health systems, or payers; or legal practice or legal tech
- Direct experience with the compliance frameworks relevant to these industries, including owning that work within an engineering org
- Exposure to both product-led growth and direct enterprise sales, and an understanding of how engineering decisions interact with each
Representative projects
- Partnering with an enterprise customer to map a core workflow—a deal-documentation process, a target-identification pipeline, a prior-authorization queue—and turning it into an engineering roadmap with a new or existing AI product
- Collaborating with research to design an evaluation framework that gives reliable signal on output quality across your domain's use cases
- Owning a platform-readiness initiative end-to-end—scoping with legal and security, defining the engineering work, and shipping it
Annual Salary
$320,000—$485,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about our policy for using AI in our application process.
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role
Anthropic's Verticals team builds AI products purpose-built for specific industries—financial services, life sciences, healthcare, and legal. Most of these teams are being built 0→1 right now: you'll be forming the team, defining the product, and shipping the first version in markets where no one has done this well yet. Where we're further along, products are already live with enterprise customers and growing fast. We're hiring Engineering Managers to lead the teams building Claude for Financial Services, Life Sciences, Healthcare, and Legal. You'll lead a team shipping AI into professional workflows—owning execution, working directly with customers and go-to-market, and helping shape where the broader Verticals group goes next. We're hiring for all four verticals through this posting. Team placement happens during the interview process based on your background, interests, and organizational need—if you have deep experience in one of these domains, let us know in your application.
About The Teams
Claude for Financial Services — Builds products for customers in investment banking, asset management, insurance, and corporate finance. Near-term work centers on deeply integrated experiences inside the tools these teams already use, with a roadmap expanding as we learn what's most useful. The team operates close to enterprise customers and close to research.
Claude for Life Sciences — We're building an agentic research platform for scientists—orchestrating specialist agents for computational biology, literature review, and regulatory review—on top of model capabilities we're investing in for biology and chemistry. The product is live with early customers and expanding fast; you'll lead engineering through that growth.
Claude for Healthcare — We're earlier here: standing up a team to build 0→1, focused initially on payer workflows (claims, prior authorization, utilization management, member communications), with groundwork for clinical applications over time. You'll be defining the product and the team at the same time.
Claude for Legal — Builds products for in-house legal teams and law firms—contract review and drafting, legal research, due diligence, and the document-heavy work that fills a lawyer's day. This team is forming now; you'll be one of the first leaders shaping what we build and who we build it with.
Responsibilities
- Lead and develop a team of engineers building new AI products for enterprise customers in your vertical
- Work closely with research to make the models better in your domain—shaping evals, surfacing failure modes, and feeding customer learnings back into model development
- Own engineering execution end-to-end: planning, prioritization, delivery quality, team health, and incident response
- Partner with sales and customer success on enterprise deals—understanding requirements, joining key conversations, and turning what you learn into engineering priorities
- Shape the roadmap with product and design, not just execute against it
- Drive the compliance and platform-readiness work your customers require, partnering with security and legal
- Recruit, onboard, and grow strong engineers; give direct feedback and build a healthy, high-performing team
You may be a good fit if you
- Have built AI products and have a practical understanding of what it takes to turn model capabilities into applications people actually use
- Are comfortable working with enterprise customers, working alongside sales and customer success and joining customer conversations
- Know the operational realities of building on platforms and integrations you don't control
- Are a skilled engineering manager who treats management as a craft—clear feedback, strong 1:1s, consistent investment in your team's growth
Strong candidates may also have
- Experience in working with research to improve domain specific model capabilities
- Experience with model evaluation frameworks and how evals inform product decisions
- Experience taking a product from 0→1—forming a team, finding product-market fit, and shipping the first version with limited precedent to lean on
- Deep domain knowledge in one of these verticals—investment banking, asset management, insurance, or corporate finance; drug discovery or computational biology; clinical operations, health systems, or payers; or legal practice or legal tech
- Direct experience with the compliance frameworks relevant to these industries, including owning that work within an engineering org
- Exposure to both product-led growth and direct enterprise sales, and an understanding of how engineering decisions interact with each
Representative projects
- Partnering with an enterprise customer to map a core workflow—a deal-documentation process, a target-identification pipeline, a prior-authorization queue—and turning it into an engineering roadmap with a new or existing AI product
- Collaborating with research to design an evaluation framework that gives reliable signal on output quality across your domain's use cases
- Owning a platform-readiness initiative end-to-end—scoping with legal and security, defining the engineering work, and shipping it
Annual Salary
$320,000—$485,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about our policy for using AI in our application process.
See all 30+ AI Product Engineer at Anthropic jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Product Engineer at Anthropic roles.
Get Access To All JobsTips for Finding AI Product Engineer Jobs at Anthropic Jobs
Frame Your Portfolio Around Safety-Aware Engineering
Anthropic evaluates AI Product Engineers on their ability to build reliable, interpretable systems. Before applying, restructure your portfolio to highlight projects where you balanced capability with measurable safety or alignment constraints, not just performance benchmarks.
Request a Defined Start Date During Offer Negotiation
H-1B transfers and new filings both require USCIS processing time. During offer negotiation, ask Anthropic's recruiting team directly whether they use premium processing, which reduces USCIS adjudication to 15 business days and protects your start date.
Prepare a Degree Equivalency Letter Early
Anthropic's AI Product Engineer roles typically require a computer science or related degree. If your credential is from outside the U.S., obtain a credential evaluation from a NACES-approved evaluator before your interview loop, not after the offer.
Use Migrate Mate to Identify Active Sponsorship Openings
Anthropic posts AI Product Engineer roles across multiple channels, but not all listings reflect current sponsorship availability. Use Migrate Mate to filter specifically for roles at Anthropic that have active visa sponsorship, so you're applying where sponsorship is confirmed.
Understand How a Cap-Exempt Employer History Affects Your Filing
If you currently work at a university or nonprofit research lab, you may be cap-exempt and can file an H-1B with Anthropic outside the April lottery window. Confirm your current employer's cap-exempt status with USCIS criteria before counting on this path.
AI Product Engineer at Anthropic jobs are hiring across the US. Find yours.
Find AI Product Engineer at Anthropic JobsFrequently Asked Questions
Does Anthropic sponsor H-1B visas for AI Product Engineers?
Yes, Anthropic sponsors H-1B visas for AI Product Engineer roles. The company also supports H-1B1 and E-3 pathways depending on your nationality. If you're filing a new H-1B cap-subject petition, the annual lottery window applies, so your start date will depend on when you entered the lottery and whether premium processing is used.
How do I apply for AI Product Engineer jobs at Anthropic?
Applications go through Anthropic's careers page. The interview process typically includes a technical screen focused on ML systems design, followed by coding rounds and a final loop that assesses your understanding of responsible AI development. Use Migrate Mate to find current AI Product Engineer openings at Anthropic that are actively sponsoring visas before you apply.
Which visa types are commonly used for AI Product Engineer roles at Anthropic?
Anthropic sponsors H-1B, H-1B1, and E-3 visas for AI Product Engineers. H-1B applies to most nationalities and requires entering the annual USCIS lottery unless you qualify for a cap-exempt transfer. H-1B1 is available to Chilean and Singaporean nationals. The E-3 is exclusive to Australian citizens and has no lottery, making it the most straightforward path for eligible candidates.
What qualifications and experience does Anthropic expect for AI Product Engineers?
Anthropic looks for engineers with a background in machine learning, systems design, and product development, typically supported by a bachelor's or graduate degree in computer science or a closely related field. Practical experience building or fine-tuning large language models, deploying inference pipelines, or working on evaluation frameworks is weighted heavily. Research contributions or prior work at an AI lab strengthens your application.
How long does the visa sponsorship process take for an Anthropic offer?
Timeline depends on your visa type and current status. An E-3 consular appointment in Australia can move within a few weeks of receiving your Labor Condition Application from the DOL. A new H-1B cap-subject petition requires winning the April lottery, with an earliest start date of October 1. Premium processing can reduce USCIS adjudication to 15 business days once a petition is filed.
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