Staff Software Engineer (AI Reliability)

Menlo Ventures; New York (NY); On-site; USD 325,000 - 485,000; Full time

Job summary

Menlo Ventures is looking for a reliability engineer to enhance AI model serving systems. You will develop Service Level Objectives, implement monitoring systems, and lead incident response efforts to ensure the reliability of AI services.

The ideal candidate will have a strong background in distributed systems and possess excellent communication skills. A Bachelor's degree is required, and experience in reliability-focused roles is a plus. Salary ranges from $325,000 to $485,000 based on experience.

Qualifications

• Strong background in distributed systems, infrastructure, or reliability.
• Excellent communication and collaboration skills.
• Experience with large-scale systems or SRE roles preferred.

Responsibilities

• Develop Service Level Objectives for model serving systems.
• Design monitoring and observability systems.
• Lead incident response and recovery efforts.
• Support reliability for critical model serving services.

Skills

Distributed systems

Incident response

Monitoring and observability

Collaboration

Education

Bachelor’s degree or equivalent

Tools

ML hardware accelerators (GPUs, TPUs)

Observability tools and frameworks

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.