Staff+ Software Engineer, Kubernetes Platform

Anthropic runs one of the industry's largest AI compute fleets, spanning multiple cloud providers and datacenters, to train, research, and serve frontier AI models. The Kubernetes Platform team owns the control plane that makes these fleets work, operating at a scale where defaults stop working. The team owns the scheduler, scales the control plane (apiserver, etcd, controllers), and builds core cluster services like service discovery.

• Own, operate, and extend the Kubernetes scheduler for accelerator fleets, including custom scheduling plugins for gang scheduling, topology awareness, and preemption.
• Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits.
• Design, build, and operate core cluster services such as service discovery.
• Build and maintain custom controllers, operators, and CRDs.
• Partner with research, training, and inference teams to turn workload requirements into platform capabilities.
• Collaborate with cloud providers on required features and escalations.
• Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs).

• 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 (beyond 'user of') into scheduler, controllers, apiserver, or operating large multi-tenant clusters.
• Demonstrated ability to debug complex issues across the stack.
• Track record of designing for reliability, correctness, and clear failure semantics.
• Strong written and verbal communication.

• Experience with Kubernetes internals or contributions (kube-scheduler, apiserver, etcd, client-go, controller-runtime).
• Experience building or operating cluster schedulers or batch systems (Kueue, Volcano, Slurm).
• Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul).
• Familiarity with ML infrastructure: GPUs, TPUs, 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.
• 10+ years of relevant industry experience.

Annual Salary: $320,000—$485,000 USD.

Minimum education: Bachelor's degree or equivalent. Location-based hybrid policy: all staff in one of our offices at least 25% of the time. Visa sponsorship: We do sponsor visas.