Staff Software Engineer, AI Reliability Engineering en Anthropic

Híbrido - London, UK

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Staff Software Engineer in AI Reliability Engineering at Anthropic is responsible for defining service level objectives for large language model serving, building monitoring and observability systems, designing high‑availability serving infrastructure across regions and cloud providers, leading incident response for critical AI services, and ensuring reliability of safeguard model serving. The role requires a strong background in distributed systems, reliability engineering, and a collaborative mindset, with experience in large‑scale model serving, ML hardware accelerators, networking optimizations, observability, chaos engineering, and open‑source tooling.

Salary

GBP 325,000 - 390,000

Requirements

Skills

  • Have strong distributed systems, infrastructure, or reliability backgrounds -- we're looking for reliability-minded software engineers and SREs.
  • Are curious and brave -- comfortable jumping into unfamiliar systems during an incident and helping drive resolution even when you don't have deep expertise yet.
  • Think holistically about how systems compose and where the seams are.
  • Can build lasting relationships across teams -- our engagement model depends on being welcomed as teammates, not outsiders with opinions.
  • Care about users and feel ownership over outcomes, even for systems you don't own.
  • Have excellent communication and collaboration skills -- you'll be partnering across the entire company.
  • Bring diverse experience -- the team's strength comes from people who've built product stacks, scaled databases, run massive distributed systems, and everything in between.
  • Have been an SRE, Production Engineer, or in similar reliability-focused roles on large scale systems.
  • Have experience operating large-scale model serving or training infrastructure (>1000 GPUs).
  • Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium).
  • Understand ML-specific networking optimizations like RDMA and InfiniBand.
  • Have expertise in AI-specific observability tools and frameworks.
  • Have experience with chaos engineering and systematic resilience testing.
  • Have contributed to open-source infrastructure or ML tooling.
  • Bachelor’s degree or an equivalent combination of education, training, and/or experience

Responsibilities

  • Develop appropriate Service Level Objectives for large language model serving systems, balancing availability and latency with development velocity.
  • Design and implement monitoring and observability systems across the token path.
  • Assist in the design and implementation of high-availability serving infrastructure across multiple regions and cloud providers.
  • Lead incident response for critical AI services, ensuring rapid recovery, thorough incident reviews, and systematic improvements.
  • Support the reliability of safeguard model serving -- critical for both site reliability and Anthropic's safety commitments.

Technologies

ML hardware accelerators (GPUs, TPUs, Trainium)ML-specific networking optimizations like RDMA and InfiniBandAI-specific observability tools and frameworksChaos engineeringOpen-source infrastructure or ML tooling

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