Staff Backend Engineer – Scalable AI Platform

Anthropic Limited

San Francisco, New York (CA, NY)

Hybrid

USD 405,000 - 485,000

Full time

5 days ago
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Benefits offered by this job

Competitive compensation
Equity donation matching
Generous vacation
Parental leave
Flexible working hours
Office space

Job summary

Anthropic Limited in San Francisco seeks experienced backend engineers to own the backend systems powering Claude API, Claude Code, and Claude.ai. You will scope multi-month projects, lead peers, and drive technical and product decisions while staying hands-on with code and models.

You'll collaborate with product, design, GTM, and research to identify capability gaps and translate model improvements into shipped features, focusing on reliability and scalability for hundreds of thousands of

Qualifications

  • 8+ years of backend or product engineering experience.
  • Experience leading multi-month projects or teams as a tech lead.
  • Strong coding fundamentals across backend systems, APIs, and integrations.
  • Ability to guide architecture and ship reliable, scalable software.

Responsibilities

  • Own backend systems powering Claude API, Claude Code, and Claude.ai.
  • Scope complex, multi-month projects and lead product decisions.
  • Ensure reliability and scalability for hundreds of thousands of users.
  • Collaborate with product, design, GTM, and research to identify capability gaps.
  • Translate model improvements into shipped features and drive architectural decisions.

Skills

Backend engineering
Product engineering
System design
APIs
Cloud infrastructure
Leadership
Cross-team collaboration
Code proficiency

Job description

Anthropic Limited in San Francisco seeks experienced backend engineers to own the backend systems powering Claude API, Claude Code, and Claude.ai. You will scope multi-month projects, lead peers, and drive technical and product decisions while staying hands-on with code and models.

You'll collaborate with product, design, GTM, and research to identify capability gaps and translate model improvements into shipped features, focusing on reliability and scalability for hundreds of thousands of

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