Staff+ Software Engineer, Enterprise AI Products

Anthropic•San Francisco, NY

1d•Hybrid

About The Position

Anthropic's Enterprise AI Products team builds what makes Claude a daily-use tool for enterprise customers across industries. We focus on organizational context and workflows (plugins, skills, connectors, webhook-triggered processes / agents). In other words, we focus on products that form the connective tissue that lets Claude operate across an organization. A big part of this work is understanding what's blocking adoption and building the capabilities that close those gaps. Much of this is being built 0→1 right now: you'll be shaping the product and the architecture in a market where no one has done this well yet. You'll be a technical leader who thinks holistically about the end-to-end customer experience, partners directly with research to push model capabilities into production, and carries real ownership over what we ship next.

Requirements

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

Nice To Haves

Experience working with research to improve domain-specific model capabilities, including evaluation frameworks
Experience building extensibility surfaces (plugins, integrations, agent tooling) that third parties or internal teams build on
Exposure to both product-led growth and direct enterprise sales

Responsibilities

Own technical design and delivery for enterprise-facing core products, end-to-end across the stack
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
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
Mentor other engineers and raise the technical bar across the team, working with influence rather than authority
Build multi-player, asynchronous agents: department-level processes that are goal-oriented, many-step, and triggered by a webhook, a form, or an email rather than a person typing