Site Reliability Engineer - AI Infrastructure

Ready to take the next step in your career?

Join a high-growth GPU cloud provider running large-scale, production GPU infrastructure for AI workloads, where engineers are trusted with real production scope from day one.

A newly created opportunity exists for a Site Reliability Engineer to keep large-scale GPU infrastructure fast, stable, and observable, working where reliability, networking, and platform engineering meet. The ideal candidate will build the automation, observability, and self-service tooling that make live GPU infrastructure more reliable, while helping shape operational standards within a small, technically strong team. This is a fully remote role open to candidates anywhere in the UK.

Ready to make a move? Get in touch and apply today!

Responsibilities:

• Own the reliability and performance of production GPU infrastructure, including the high-performance networking that underpins it.
• Design, build and maintain observability, monitoring and dashboards. Improve signal quality through correlation, enrichment, suppression and deduplication.
• Build Python-based automation for incident triage, runbook execution and routine operational tasks. Maintain version-controlled runbook-as-code and automation libraries.
• Integrate observability, ITSM and infrastructure APIs to enrich alerts and automate end-to-end operational workflows.
• Deliver internal tools and self-service capabilities, including CLI utilities, ChatOps integrations and dashboards.
• Turn post-incident learnings into better tooling and operational standards. Build safe, auditable automation for higher-risk actions, with appropriate approval controls.

Skills/Must have:

• Experience: A proven track record as an SRE or Production/Infrastructure Engineer, with hands-on responsibility for GPU infrastructure in a live production environment.
• Core Tech/Domain: Production GPU infrastructure operations (for example, GPU cloud, AI/ML compute clusters or HPC). Strong Python for automation and tooling.
• Methodology/Protocols: Deep observability and dashboarding experience (for example, Prometheus, Grafana or similar), alert design and noise reduction, incident management, and runbook-as-code practices.
• Soft Skills: An ownership mindset, calm under incident pressure, and the discipline to fix root causes through automation rather than repeating manual fixes. You should be comfortable working autonomously in a remote team.

Desirable Skills:

• Networking reliability experience, particularly low-latency networking and InfiniBand
• Platform engineering background (Kubernetes, infrastructure-as-code, internal developer platforms)
• HPC infrastructure exposure (for example, Slurm-managed clusters or research computing environments)
• ChatOps and ITSM integration experience (for example, Slack/Teams bots, ServiceNow or Jira Service Management APIs)

Benefits:

• Fully remote working (UK-based)
• Full benefits package to be confirmed

Salary:

• £120,000