Anthropic· Engineering & Design - Product· New York City, NY; San Francisco, CA | New York City, NY
Engineering Manager, Vertical AI Products (Multiple Roles)
Classified Tasks (36)
Automate 0%Augment 69%Human-Only 31%
Augment (25)
AI assists, human decides
Define the product for the vertical
leadership
Ship the first version of the product to market
operational
Plan engineering work and releases end-to-end
operational
Prioritize engineering tasks and roadmap items
leadership
Ensure delivery quality of engineering outputs
operational
Manage incident response for production issues
operational
Collaborate with research to improve models for the domain
technical
Shape model evaluations (evals) for domain-specific performance
analytical
Surface model failure modes to engineering and research teams
communication
Feed customer learnings back into model development
communication
Gather and document enterprise customer requirements
communication
Translate customer and sales learnings into engineering priorities
operational
Co-create the product roadmap with product and design teams
leadership
Drive compliance work required by enterprise customers
operational
Ensure platform-readiness for enterprise deployment
technical
Recruit engineers for the team
leadership
Onboard new engineers into the organization and codebase
administrative
Collaborate with go-to-market teams on product launches and customer strategy
communication
Build deeply integrated experiences inside customers' existing tools (financial services)
technical
Build an agentic research platform for scientists (life sciences)
technical
Orchestrate specialist agents for computational biology, literature review, and regulatory review
technical
Integrate biology and chemistry model capabilities into product workflows
technical
Design and implement solutions for payer workflows: claims, prior authorization, utilization management, and member communications
technical
Lay technical and product groundwork for future clinical applications
technical
Scale live products and engineering efforts with enterprise customer growth
operational
Human-Only (11)
Requires human judgment
Form the engineering team for a new vertical
leadership
Lead a team building AI products for enterprise customers in the vertical
leadership
Maintain team health through management and process
leadership
Partner with sales and customer success on enterprise deals
communication
Join key customer conversations and demos
communication
Partner with security and legal on compliance and platform readiness
communication
Grow and develop engineers through coaching and feedback
leadership
Give direct performance and career feedback to engineers
leadership
Build and maintain a healthy, high-performing engineering team
leadership
Shape the strategic direction of the Verticals group
leadership
Stand up a team to build 0→1 healthcare products focused on payer workflows
leadership
Job description
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, and Healthcare . 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. 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 A