Staff+ Software Engineer, Enterprise Knowledge Work

About the role

Anthropic's Enterprise Knowledge Work team builds the products that help enterprise knowledge workers collaborate deeply with Claude for major parts of their work.

Over the past year, AI has transformed how software engineering happens; for the rest of knowledge work, though, using AI still mostly means answering questions and producing first drafts — a small slice of the actual job.

We're building toward something bigger: people and agents working together on every core work objective, from first idea to finished product, and the recurring work of a team running with Claude in the loop instead of a person pushing every step. It's an enormous space, it's early, and no one has built it well yet.

You'll help decide what these products are, not just how they're built — the product questions are as open as the architecture ones — and you'll see your work land with real teams at the world's largest enterprises.

What you'll do

• 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 the core primitives that enable knowledge workers across industries and roles to meaningfully leverage Claude

You may be a good fit if you

• 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 customer-facing 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

Strong candidates may also have

• Experience working with research to improve domain-specific model capabilities, including evaluation frameworks
• Experience as startup founders or early-stage employees