Staff Software Engineer, AI Reliability

at Anthropic

📍 New York City, United States
📍 San Francisco, United States
📍 Seattle, United States

USD 325,000-485,000 per year

SENIOR

✅ Hybrid

✅ Visa Sponsorship

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 6 API Communication @ 7 Distributed Systems @ 7 GPU InfiniBand @ 4 LLM Machine Learning Networking @ 4 Observability @ 6 SRE @ 7

Details

Anthropic’s AI Reliability Engineering team partners with teams across the company to improve reliability across critical serving paths, including the SDK, network, API layers, serving infrastructure, and accelerators. The team works alongside partner teams during incidents and on projects to make the systems delivering Claude more robust and resilient.

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 designing and implementing 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, which is critical for site reliability and Anthropic’s safety commitments.

Requirements

Strong background in distributed systems, infrastructure, or reliability, as a reliability-minded software engineer or SRE.
Comfort jumping into unfamiliar systems during incidents and helping drive resolution.
Ability to think holistically about how systems compose and where their seams are.
Strong communication and collaboration skills, with the ability to partner across the company.
Ownership of user and system outcomes, including systems outside of direct ownership.
A bachelor’s degree or equivalent combination of education, training, and experience in a field relevant to the role, demonstrated through coursework, training, or professional experience.

Preferred Qualifications

Experience as an SRE, Production Engineer, or in a similar reliability-focused role on large-scale systems.
Experience operating large-scale model serving or training infrastructure involving more than 1,000 GPUs.
Experience with ML hardware accelerators such as GPUs, TPUs, or Trainium.
Understanding of ML-specific networking optimizations such as RDMA and InfiniBand.
Expertise with AI-specific observability tools and frameworks.
Experience with chaos engineering and systematic resilience testing.
Contributions to open-source infrastructure or ML tooling.

Benefits

Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and an office environment for collaboration. Staff are currently expected to work from one of the company’s offices at least 25% of the time, though some roles may require more office time.

Anthropic sponsors visas for this role when possible and makes reasonable efforts to obtain a visa for candidates who receive an offer, with support from an immigration lawyer.