Staff+ Software Engineer, Public Sector at Anthropic

Hybrid - Remote-Friendly, United States; San Francisco, CA | New York City, NY | Washington, DC

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Anthropic is bringing Claude to the U.S. government and allied democracies, and we’re looking for startup‑minded engineers to grow our public sector engineering team. This is a small team with large surface area. You’ll work across the stack to take products from 0 to 1 and beyond. We are looking for product‑ and civic‑minded engineers with a track record of building and scaling great products. The opportunities outpace our ability to build them all, so the right candidate thrives on sharp judgment, prioritization, and focus.

Salary

USD 405,000 - 485,000

Requirements

Skills

  • Experience building AI products and a working intuition for their capabilities and limitations
  • Strong technical track record building and shipping enterprise- or government-grade products
  • Excellent cross‑functional collaboration skills
  • 8+ years of experience as a full stack or backend software engineer
  • Startup experience, particularly in scaling products from zero to one
  • Experience partnering with sales, customer success, and professional services teams to drive product adoption
  • Experience deploying software on government networks
  • Active federal security clearance (Secret or above)

Responsibilities

  • Architect and ship deployments that meet public sector compliance and security requirements, from FedRAMP to classified networks
  • Build AI applications tailored to government workflows by developing deep understanding of how agencies actually operate
  • Partner with research and safeguards teams to evaluate and improve Claude for government use cases
  • Work directly with government customers and internal go‑to‑market teams to turn requirements into technical and product roadmaps
  • Design scalable systems for deployment, user management, and administrative controls across constrained environments
  • Create clarity and technical direction in a fast‑moving environment with unique constraints

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