Staff+ Software Engineer, Vertical AI Products (Multiple Roles)

Anthropic
San Francisco, CA, USA2026-07-02

About the job

Anthropic's Verticals team builds AI products purpose-built for specific industries — financial services, science, healthcare, and the broader enterprise. Most of these teams are being built 0→1 right now: you'll be shaping the product and the architecture 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.

Responsibilities

Own technical design and delivery for a core piece of one of these vertical or enterprise products, end-to-end across the stack

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

Partner with product, design, and go-to-market to turn enterprise customer workflows into shipped product, not just execute against a spec

Set technical direction and standards for your team — architecture, code quality, and how the team builds

Work directly with enterprise customers and sales during key conversations, translating what you learn into engineering priorities

Mentor other engineers and raise the technical bar across the team, working with influence rather than authority

Qualifications

Minimum

Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level

Have led the design and delivery of complex enterprise or B2B products across the full stack

Have built AI products and know what it takes to turn model capabilities into applications people actually use

Are comfortable working directly with enterprise customers and translating what you learn into technical decisions

Have built products from 0 to 1 in fast-moving environments, and can set technical direction with limited precedent to lean on

Drive cross-team alignment to ship impactful work, with influence over authority

Preferred

Experience working with research to improve domain-specific model capabilities, including evaluation frameworks

Deep domain knowledge in one of these areas: investment banking, asset management, insurance, or corporate finance; scientific research or computational biology; clinical operations, health systems, or payers; or enterprise platform work

Exposure to both product-led growth and direct enterprise sales