Staff Software Engineer, AI Reliability Engineering

• Partner with teams across Anthropic to improve reliability across the most critical serving paths — every hop from the SDK through the network, API layers, serving infrastructure, and accelerators and back. • 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 and lead incident response for critical AI services. • Assist in the design of high-availability serving infrastructure across multiple regions and cloud providers. • Support the reliability of safeguard model serving — critical for both site reliability and Anthropic's safety commitments.

• Have a strong distributed systems, infrastructure, or reliability background — this role is for reliability-minded software engineers and SREs. • Be curious and brave — comfortable jumping into unfamiliar systems during an incident and helping drive resolution without deep prior expertise. • Think holistically about how systems compose and where the seams are. • Be able to build lasting relationships across teams — the engagement model depends on being welcomed as a teammate, not an outsider with opinions. • Care about users and feel ownership over outcomes even for systems you don't own. • Have excellent communication and collaboration skills for company-wide partnering.

• Have experience as an SRE, Production Engineer, or in similar reliability-focused roles on large-scale systems. • Have experience operating large-scale model serving or training infrastructure at more than 1,000 GPUs. • Have experience with ML hardware accelerators such as GPUs, TPUs, or Trainium. • Understand ML-specific networking optimisations 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.

• Develop SLOs for large language model serving systems balancing availability, latency, and development velocity. • Design and implement monitoring and observability systems across the token path. • Lead incident response for critical AI services, ensuring rapid recovery, thorough incident reviews, and systematic improvements. • Assist in designing high-availability serving infrastructure across multiple regions and cloud providers. • Support reliability of safeguard model serving for both site reliability and safety commitments. • Zoom out across team boundaries to identify systemic reliability risks and improvements.

• Earn £325,000–£390,000 per year. • Receive visa sponsorship — Anthropic retains an immigration lawyer and makes every reasonable effort to support visa applications. • Access optional equity donation matching, generous vacation and parental leave, and flexible working hours. • Work across the full serving stack at one of the world's most important AI companies, with unique cross-cutting exposure to the systems that matter most.

Anthropic is a public benefit corporation headquartered in San Francisco, with a mission to create reliable, interpretable, and steerable AI systems. AIRE (AI Reliability Engineering) partners with teams across Anthropic to improve reliability across the most critical serving paths — ensuring Claude remains reliable for everyone who depends on it by looking holistically at reliability as an emergent phenomenon across the entire system.