Staff SRE, AI Infrastructure

Overview

In this role, you will strengthen the reliability of Wayve’s large-scale AI infrastructure, spanning cloud, Kubernetes, and GPU compute. You’ll partner with cross-functional teams to turn operational problems into durable engineering solutions, improving observability, deployment safety, and capacity planning. Your work will directly impact the resilience of distributed AI training and scalable platform operations. This is a hands-on opportunity to shape production-readiness practices in a fast-growing AI driving company.

Pay / Benefits

• Salary benchmarked against market annually
• Meaningful equity
• Relocation support and visa sponsorship
• Hybrid working with core hours
• Learning and development budgets
• Comprehensive health and dental benefits; pension/retirement; wellbeing and team socials

Responsibilities

• Identify reliability risks across compute, networking, storage, and distributed workloads and implement durable engineering solutions
• Improve observability, deployment safety, capacity planning, and incident learning; drive adoption of SLOs and production-readiness practices
• Enhance GPU node health detection and automated recovery; strengthen resilience of distributed AI training
• Develop continuous GitOps delivery using Argo CD or Flux; improve Kubernetes scheduling and autoscaling
• Create reusable self-service capabilities to scale platform operations for cross-team use

Key requirements

• Hands-on experience owning reliability of large-scale cloud, Kubernetes, or distributed infrastructure
• Experience coding, automating, configuring, or troubleshooting production systems
• Proficiency in Python or Go, IaC, CI/CD or GitOps, and modern observability practices
• Understanding of distributed systems failure modes across compute, networking, storage
• Direct experience with GPU, ML-training, or HPC infrastructure is valuable but not required

• Collaborative cross-team working
• Problem solving under pressure
• Proactive ownership and initiative
• Python or Go
• Infrastructure as Code
• CI/CD or GitOps

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