About this opportunity
Menlo Ventures lists this Staff Software Engineer (AI Reliability) opportunity in new york, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
About The Role
AIRE (AI Reliability Engineering) partners with teams across Anthropic to improve reliability across our most critical serving paths – every hop from the SDK through our network, API layers, serving infrastructure, and accelerators and back. We jump into the trenches alongside partner teams to make the systems that deliver Claude more robust and resilient, be it during an incident or 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 – and it means few teams at Anthropic offer this kind of dynamic, cross‑cutting exposure to the systems that matter most.
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
You May Be a Good Fit If You
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
Strong Candidates May Also
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 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
Annual Salary
$325,000—$485,000 USD
Logistics
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! However, we aren’t able to successfully sponsor visas for every role and every candidate. If we make you an offer, we will make every reasonable effort to get you a visa and retain an immigration lawyer to help with this.
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Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.