Staff + Senior Software Engineer, Inference Infrastructure (AI)

Location: San Francisco, CA; New York City, NY; or Seattle, WA. Hybrid policy: staff are expected to work from one of the offices at least 25% of the time; some roles may require more office attendance.

Annual salary: $320,000–$485,000 USD

Company

Anthropic builds reliable, interpretable, and steerable AI systems intended to be safe and beneficial for users and society.

What you will do

• Design, build, and maintain distributed systems serving Claude to millions of users worldwide.
• Develop intelligent request routing, load balancing, traffic management, autoscaling, and fleet orchestration across thousands of AI accelerators.
• Build and operate production-grade deployment pipelines for releasing new models reliably.
• Provide high-performance inference infrastructure for next-generation model research.
• Integrate new AI accelerator platforms and support inference for new model architectures.
• Analyze observability data and tune performance across multi-region production deployments.

Requirements

• Significant software engineering experience, particularly with distributed systems.
• Experience with high-performance, large-scale distributed systems.
• Experience implementing and deploying machine learning systems at scale.
• Strong problem-solving flexibility, impact orientation, and willingness to work beyond a narrowly defined job description.
• Bachelor’s degree or equivalent combination of education, training, and experience in a relevant field.
• Visa sponsorship is available, subject to role and candidate eligibility.

Nice to have

• Experience with load balancing, request routing, or traffic management systems.
• Familiarity with LLM inference optimization, batching, and caching strategies.
• Experience with Kubernetes and AWS, GCP, or Azure.
• Proficiency in Python or Rust.

Culture & Benefits

• Collaborative work across research, engineering, policy, and business functions.
• Focus on large-scale AI research, technical impact, and the societal implications of AI systems.
• Flexible working hours and an office environment for collaboration.
• Competitive compensation, optional equity donation matching, generous vacation, and parental leave.