Staff SRE, AI Infrastructure

Wayve

. Identify reliability risks with infrastructure engineers .

Posted 11/9/2026full-timeLondon • United KingdomLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in ensuring the reliability of large-scale cloud and Kubernetes infrastructure, with a strong focus on automation, observability, and incident management. Proficient in coding and troubleshooting production systems, particularly in Python or Go, while enhancing platform operations through GitOps practices.

Highest-signal resume keywords

Reliability EngineeringKubernetes ManagementPython ProgrammingGitOps ImplementationObservability Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Infrastructure As CodeCI/CDTroubleshootingCapacity PlanningAutomationDistributed SystemsGPU InfrastructureML-TrainingHPC InfrastructureSLOs

Soft Skills

CollaborationProblem-Solving

Tools & Technologies

Argo CDFluxKubernetesGitOps

Industry Keywords

Cloud InfrastructureObservabilityDistributed WorkloadsProduction ReadinessIncident Management

Tech Stack

Tools & technologies

CloudFluxKubernetesNode.jsPythonGo

About the role

Key responsibilities & impact

Identify reliability risks with infrastructure engineers
Turn recurring operational problems into durable engineering solutions
Improve observability, automation, deployment safety, and capacity planning
Improve incident learning and help teams adopt effective SLOs and production-readiness practices
Troubleshoot complex failures across compute, networking, storage, and distributed workloads
Improve GPU node health detection and automated recovery
Strengthen the resilience of distributed AI training
Develop continuous GitOps delivery using platforms such as Argo CD or Flux
Enhance Kubernetes scheduling, autoscaling, policy enforcement, and resource efficiency
Build forecasting for GPU and storage capacity
Create reusable self-service capabilities for reliable platform operations at scale

Requirements

What you’ll need

Hands-on experience owning the reliability of large-scale cloud, Kubernetes, or distributed infrastructure
Recent hands-on experience coding, automating, configuring, or troubleshooting production systems
Comfortable working in Python or Go
Experience with infrastructure as code
Experience with CI/CD or GitOps
Experience with modern observability practices
Understanding of distributed-systems failure modes across compute, networking, and storage
Ability to demonstrate measurable improvements to reliability, performance, capacity, or cost
Ability to collaborate effectively across teams
Direct experience with GPU, ML-training, or HPC infrastructure is valuable, but comparable large-scale platform experience is relevant

Benefits

Comp & perks

Salaries benchmarked against the market annually
Meaningful equity, sharing in the ownership and long term success of Wayve
Relocation support and visa sponsorship where applicable
Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
Learning and development budgets with support for training, conferences and growth
Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more