Staff+ Software Engineer, Enterprise AI Products

Anthropic Anthropic · AI Frontier · San Francisco, CA · Engineering & Design - Product

Staff+ Software Engineer for Anthropic's Enterprise AI Products team, focusing on building organizational context and workflows (plugins, skills, connectors, webhook-triggered agents) to make Claude a daily-use tool for enterprise customers. This role involves technical leadership, end-to-end product delivery, customer interaction, and close collaboration with research to integrate model capabilities into production.

What you'd actually do

  1. Own technical design and delivery for enterprise-facing core products, end-to-end across the stack
  2. Partner with product, design, and go-to-market to turn enterprise customer workflows into shipped product, not just execute against a spec
  3. Set technical direction and standards for your team: architecture, code quality, and how the team builds
  4. Work directly with enterprise customers and sales during key conversations, translating what you learn into engineering priorities
  5. 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

Skills

Required

  • 8+ years of software engineering experience
  • 2+ years at a Staff or equivalent technical leadership level
  • led the design and delivery of complex enterprise or B2B products across the full stack
  • built AI products
  • comfortable working directly with enterprise customers
  • built products from 0 to 1 in fast-moving environments

Nice to have

  • Experience working with research to improve domain-specific model capabilities, including evaluation frameworks
  • Experience building extensibility surfaces (plugins, integrations, agent tooling)
  • Exposure to both product-led growth and direct enterprise sales

What the JD emphasized

  • building products from 0 to 1
  • set technical direction with limited precedent

Other signals

  • building organizational context and workflows
  • shipping AI products
  • customer-facing AI products