Staff Software Engineer AI Reliability Engineering

Humanloop; Greater London; On-site; GBP 57,000 - 73,000; Full time

Benefits offered by this job

Competitive compensation and benefits

Equity donation matching (optional)

Generous vacation and parental leave

Flexible working hours

Hybrid policy: in-office presence 25%+

Visa sponsorship where possible

Job summary

Anthropic in the UK seeks an experienced reliability-focused engineer to own large-scale AI serving infrastructure. You will define SLAs, build robust monitoring, and drive fast incident response across multiple regions. This role emphasizes cross-team collaboration, ownership, and impact in a highly technical environment.

You should have a strong background in distributed systems, production engineering, or SRE, with a focus on reliability in AI workloads and large-scale model serving.

Qualifications

• Bachelor's degree or equivalent required.
• Experience with distributed systems and reliability concepts.
• Strong communication and collaboration skills; ownership mindset.

Responsibilities

• Define and monitor service level objectives for AI serving systems.
• Design and implement monitoring and observability across token paths.
• Help build high-availability serving infrastructure across regions/clouds.
• Lead incident response for critical AI services and drive improvements.
• Support reliability of safeguard model serving and safety commitments.

Skills

Distributed systems

Reliability engineering

SRE

Communication

Collaboration

Ownership

Open-source contributions

Incident response

Education

Bachelor's degree

Field relevant to role

Tools

AI observability tools

Chaos engineering tooling

Observability frameworks

Large-scale model serving infrastructure

GPU/ML accelerators

Job description

Salary: £57,000 - 73,000 per year

Requirements

• We are looking for strong distributed systems, infrastructure, or reliability backgrounds, including reliability-minded software engineers and SREs.
• We value candidates who are curious and brave, and who are comfortable jumping into unfamiliar systems during an incident to help drive resolution.
• We look for people who think holistically about how systems compose and where the seams are.
• We need someone who can build lasting relationships across teams and work as a trusted teammate.
• We value people who care about users and feel ownership over outcomes, even for systems they do not own.
• Excellent communication and collaboration skills are important, as you will partner across the company.
• We value diverse experience across product stacks, databases, distributed systems, and related technical domains.
• A bachelors degree or an equivalent combination of education, training, and/or experience is required.
• A field relevant to the role through coursework, training, or professional experience is required.
• Years of experience should align with the internal job level requirements for the position.
• Strong candidates may also have experience as an SRE, Production Engineer, or in similar reliability-focused roles on large-scale systems.
• Experience operating large-scale model serving or training infrastructure, including environments with more than 1,000 GPUs, is a plus.
• Experience with ML hardware accelerators such as GPUs, TPUs, or Trainium is a plus.
• Knowledge of ML-specific networking optimizations such as RDMA and InfiniBand is a plus.
• Expertise in AI-specific observability tools and frameworks is a plus.
• Experience with chaos engineering and systematic resilience testing is a plus.
• Contributions to open-source infrastructure or ML tooling are a plus.

Responsibilities

• We develop appropriate Service Level Objectives for large language model serving systems, balancing availability and latency with development velocity.
• We design and implement monitoring and observability systems across the token path.
• We assist in the design and implementation of high-availability serving infrastructure across multiple regions and cloud providers.
• We lead incident response for critical AI services, ensuring rapid recovery, thorough incident reviews, and systematic improvements.
• We support the reliability of safeguard model serving, which is critical for both site reliability and our safety commitments.

Technologies

• AI
• API
• Cloud
• Hardware
• InfiniBand
• Support
• Model Serving
• Network
• RDMA

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• A lovely office space in which to collaborate with colleagues
• A hybrid policy with in-office presence expected at least 25% of the time
• We also sponsor visas where possible

We encourage applicants from underrepresented groups to apply.

More

We are Anthropic, a public benefit corporation headquartered in San Francisco, and our mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for our users and for society. Our AIRE (AI Reliability Engineering) team works across Anthropic to improve reliability across our most critical serving paths, from the SDK through our network, API layers, serving infrastructure, and accelerators and back. We work in a highly collaborative environment with dynamic, cross-cutting exposure to the systems that matter most, and we value communication, teamwork, and impact. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, a lovely office space in which to collaborate with colleagues, and a hybrid policy with in-office presence expected at least 25% of the time. We also sponsor visas where possible.