Staff Software Engineer, Kubernetes Platform

Responsibilities

We are representing a confidential AI organization seeking a Staff Software Engineer to own and operate their Kubernetes platform supporting large-scale compute infrastructure. You will work on one of the industry's largest Kubernetes deployments, spanning multiple cloud providers and handling thousands of accelerators simultaneously.

In this role, you will:

• Own, operate, and extend the Kubernetes scheduler for accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption
• Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and identify bottlenecks before they impact operations
• Design, build, and operate core cluster services such as service discovery that every workload depends on
• Build and maintain custom controllers, operators, and Custom Resource Definitions (CRDs)
• Partner with research, training, and inference teams to understand workload requirements and translate them into platform capabilities
• Collaborate with cloud providers on feature requirements and escalations
• Participate in on-call rotation, lead incident response, and design reliability processes including postmortems, runbooks, and SLOs

What We're Looking For

Required qualifications:

• Significant software engineering experience building and operating production distributed systems
• Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++)
• Deep, hands-on Kubernetes experience extending well beyond user-level into scheduler, controllers, apiserver, or operating large multi-tenant clusters
• Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes
• Track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on
• Strong written and verbal communication skills; comfort building consensus with internal stakeholders

Preferred qualifications:

• Experience with Kubernetes internals or contributions: kube-scheduler/scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar
• Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents)
• Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments)
• Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL
• Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code
• Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF
• 12+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects

Education: Bachelor's degree or an equivalent combination of education, training, and/or experience in a field relevant to the role

Location: London – Hybrid policy requiring office presence at least 25% of the time

Visa sponsorship: The client does sponsor visas and will make every reasonable effort to support successful candidates, working with immigration counsel as needed

How We Work With You

Our talent team at Get A Job.ai partners with leading organizations to connect exceptional engineering talent with transformative opportunities. When you apply through our platform:

• You submit your application directly on getajob.ai
• One of our experienced recruiters will screen your profile and conduct an initial conversation
• We present qualified candidates to our client for consideration
• We guide you through each stage of the interview process

Important: Please do not attempt to contact the client directly. All communication should flow through Get A Job.ai to ensure a smooth and professional process.

Pay

This is a high-impact staff-level position. Compensation details will be discussed during the screening process with our recruiting team.

Equal Opportunity: Get A Job.ai is committed to fair and equitable recruiting practices. We encourage applications from candidates of all backgrounds and experiences. Research shows that underrepresented groups may hesitate to apply unless they meet every qualification—we urge you to apply if this work excites you, even if your background doesn't match every point listed above.