Software Engineer, AI Reliability San Francisco, CA NY | Seattle, WA

Staff + Sr. Software Engineer, AI Reliability About the Role

AIRE (AI Reliability Engineering) partners with teams across Anthropic to improve reliability across our most critical serving paths—from the SDK through our network, API layers, serving infrastructure, accelerators, and back. We jump into the trenches alongside partner teams to make the systems that deliver Claude more robust and resilient, whether during an incident or while collaborating on projects. Reliability here is an emergent phenomenon that transcends any single team's boundaries, so someone has to zoom out and look at the whole picture.

That’s us—meaning few teams at Anthropic offer this kind of dynamic, cross‑cutting exposure to the systems that matter most.

• 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

• Have strong distributed systems, infrastructure, or reliability backgrounds—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—partnering across the entire company
• Bring diverse experience—from product stacks, scaled databases, 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 (over 1000 GPUs)
• Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium)
• Understand ML‑specific networking optimizations like RDMA and Infini Band
• 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

The annual compensation range for this role is $325,000 – $485,000 USD.

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience.

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience.

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position.

Location‑based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas, and if we make you an offer we will make every reasonable effort to obtain a visa.

Equal Employment Opportunity Policy

As set forth in Anthropic’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.