# Staff Software Engineer, AI Reliability Engineering

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** London, United Kingdom, Dublin, Ireland
**Role:** DevOps / SRE
**Salary:** €235k – €295k/yr
**Experience:** 7+ years
**Skills:** Distributed Systems, Infrastructure, Site Reliability Engineering, Service Level Objectives, Monitoring, Observability, High Availability, Incident Response, Cloud Providers, Gpus, Tpus, Trainium, Rdma, InfiniBand, Chaos Engineering
**Posted:** 2026-08-03

> Staff software engineer responsible for improving reliability across Anthropic’s AI serving systems, from SDK and network layers through infrastructure and accelerators. The role focuses on SLOs, observability, high availability, incident response, and resilience across distributed systems.

## Job Description

## Responsibilities
- Develop appropriate **Service Level Objectives (SLOs)** 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.

## Requirements
- Strong background in distributed systems, infrastructure, or reliability engineering.
- Experience as a reliability-minded software engineer or site reliability engineer.
- Ability to work effectively in unfamiliar systems during incidents and help drive resolution.
- Holistic understanding of how systems compose and where system seams exist.
- Ability to build lasting relationships and collaborate across teams.
- Strong communication and collaboration skills.
- Bachelor's degree or equivalent combination of education, training, and experience.

## Nice-to-haves
- 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, including GPUs, TPUs, or Trainium.
- Understanding of ML-specific networking optimizations such as RDMA and InfiniBand.
- Expertise in AI-specific observability tools and frameworks.
- Experience with chaos engineering and systematic resilience testing.
- Contributions to open-source infrastructure or ML tooling.

## Compensation and Benefits
- Annual salary: **€235,000–€295,000 EUR**
- Competitive compensation and benefits.
- Optional equity donation matching.
- Generous vacation and parental leave.
- Flexible working hours.

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