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Staff + Sr. Software Engineer, Scaling

Anthropic · San Francisco

Senior 🇬🇧 English
cloud platforms load balancing request routing autoscaling orchestration deployment pipelines

Job description

About the role

Anthropic’s Inference team is looking for a Staff/Senior Software Engineer to design and scale the distributed systems that power Claude, serving millions of users worldwide. You will work on high‑performance inference infrastructure across multiple cloud providers and AI accelerator families.

Key responsibilities

  • Design, build, and maintain distributed systems that deliver Claude at scale.
  • Develop resilient, real‑time adaptive systems for production workloads.
  • Create intelligent request routing, load‑balancing, and traffic‑management across thousands of accelerators and cloud providers.
  • Optimize compute efficiency and cost through autoscaling and orchestration of production, research, and experimental workloads.
  • Build and operate production‑grade deployment pipelines for releasing new models.
  • Provide high‑performance inference infrastructure to enable next‑generation model research.
  • Integrate new AI accelerator platforms and support inference for emerging model architectures.

Required profile

  • Significant software engineering experience, especially with distributed systems.
  • Results‑oriented with a bias toward flexibility and impact.
  • Willingness to take on tasks beyond the core description.
  • Interest in learning machine‑learning systems and infrastructure.
  • Ability to thrive where technical excellence drives business and research outcomes.
  • Awareness of societal impact of AI work.
  • Experience with high‑performance, large‑scale distributed systems (preferred).
  • Experience deploying machine‑learning systems at scale (preferred).
  • Experience with load balancing, request routing, or traffic management (preferred).
  • Familiarity with LLM inference optimization (preferred).

Required skills

  • Distributed systems engineering
  • Cloud platforms (multiple providers)
  • AI accelerator integration
  • Load balancing and request routing
  • Autoscaling and orchestration
  • Deployment pipelines for model releases
  • High‑performance inference infrastructure

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Source : ats:greenhouse

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Published 4 weeks ago

Expires 4 weeks from now

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Anthropic

San Francisco