Staff Software Engineer, AI Reliability Engineering

SignalAI; Greater London; Hybrid; GBP 325,000 - 390,000; Full time

Benefits offered by this job

Visa sponsorship

Job summary

Anthropic is seeking a seasoned Reliability Engineer to join our AI Reliability Engineering (AIRE) team. You will help keep Claude reliable across our services, SDK, network, and infrastructure, collaborating with engineers, researchers, policy experts, and product teams.

You will design and implement monitoring, define SLOs, and lead incident responses across multi-region deployments, ensuring high availability while maintaining safety commitments, with a location-based hybrid policy and visa

Qualifications

• Strong distributed systems, infrastructure, or reliability backgrounds.
• Willingness to jump into unfamiliar systems during incidents.
• Ability to collaborate across teams and communicate well.

Responsibilities

• Develop Service Level Objectives for large language model serving systems.
• Design and implement monitoring and observability across token path.
• Assist in designing high-availability serving infrastructure across regions and clouds.
• Lead incident response for critical AI services.
• Support reliability of safeguard model serving for safety commitments.

Skills

Distributed systems

Reliability engineering

SRE

Software engineering

Incident response

Education

Bachelor’s degree or equivalent

Job description

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About The Role

Claude has your back. AIRE has Claude's. Help us keep Claude reliable for everyone who depends on it.

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.

Who may be a good fit

• 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 (>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 - £390,000 GBP

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Logistics

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

• 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. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

Your safety matters to us

To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How We’re Different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long‑term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We’re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

Guidance on Candidates' AI Usage

Learn about our policy for using AI in our application process.

• optional equity donation matching


• generous vacation and parental leave


• flexible working hours


• lovely office space in which to collaborate with colleagues

We believe AI will have a transformative impact on the world

We’re seeking exceptional candidates who collaborate thoughtfully with Claude to realize this vision. At the same time, we want to understand your unique skills, expertise, and perspective through our hiring process. We invite you to review our AI partnership guidelines for candidates and confirm your understanding by selecting “Yes.”

Diversity and Inclusion Statement

We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.