Engineering Manager, Vertical AI Products (Multiple Roles)

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