> Markdown version of [/jobs/ext/2824636-senior-software-engineer-ai-reliability-engineering-london-uk](https://www.wearedevelopers.com/jobs/ext/2824636-senior-software-engineer-ai-reliability-engineering-london-uk). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, AI Reliability Engineering London, UK - **Company:** Anthropic - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Software as a Service, Distributed Systems, Monitoring of Systems, InfiniBand, Machine Learning, Open Source Technology, Remote Direct Memory Access, Reliability Engineering, Graphics Processing Unit (GPU), AI Platforms, Deployment Automation, Hardware Acceleration - **Published:** September 10, 2026 - **Apply:** https://www.collegerecruiter.com/job/2840576781-senior-software-engineer-ai-reliability-engineering-london-uk ## About the Role * Have extensive experience with distributed systems observability and monitoring at scale * Understand the unique challenges of operating AI infrastructure, including model serving, batch inference, and training pipelines * Have proven experience implementing and maintaining SLO/SLA frameworks for business-critical services * Are comfortable working with both traditional metrics (latency, availability) and AI-specific metrics (model performance, training convergence) * Have experience with chaos engineering and systematic resilience testing * Can effectively bridge the gap between ML engineers and infrastructure teams * Have excellent communication skills., * Have experience operating large-scale model training infrastructure or serving infrastructure (>1000 GPUs) * Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium, e.g.) * Understand ML-specific networking optimizations like RDMA and InfiniBand. * Have expertise in AI-specific observability tools and frameworks * Understand ML model deployment strategies and their reliability implications * Have contributed to open-source infrastructure or ML tooling, Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. 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. ## Description The AIRE Serving team is responsible for elevating the reliability of Anthropic's token path from client to inference servers and back. The team has wide latitude to drive improvements to our expanding SaaS and product surface, uplevel reliability mindsets across Anthropic, and partner with teams internally to build more robust and reliable systems. The breadth and depth of the technical challenges someone joining this team will encounter will be career defining and we are still writing the playbooks. We are at the center of ensuring our customers have a consistently excellent experience., * Develop appropriate Service Level Objectives for large language model serving and training systems, balancing availability/latency with development velocity. * Design and implement monitoring systems including availability, latency and other salient metrics. * Assist in the design and implementation of high-availability language model serving infrastructure capable of handling the needs of millions of external customers and high-traffic internal workloads. * Develop and manage automated failover and recovery systems for model serving deployments across multiple regions and cloud providers. * Lead incident response for critical AI services, ensuring rapid recovery and systematic improvements from each incident * Build and maintain cost optimization systems for large-scale AI infrastructure, focusing on accelerator (GPU/TPU/Trainium) utilization and efficiency ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [This App Reached 10,000 Users in One Week. Here's How.](https://www.wearedevelopers.com/videos/100329-this-app-reached-10-000-users-in-one-week-here-s-how) - [The Gashlycrumb Tinies of AI Networking You Must Know (or Languish!)](https://www.wearedevelopers.com/videos/2067-the-gashlycrumb-tinies-of-ai-networking-you-must-know-or-languish) - [Staying Safe in the AI Future](https://www.wearedevelopers.com/videos/521-staying-safe-in-the-ai-future) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Trustworthy AI Starts at Deployment: 5 Checks Before You Ship](https://www.wearedevelopers.com/magazine/753-trustworthy-ai-starts-at-deployment-5-checks-before-you-ship) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)