Location
London (Hybrid - minimum 25% office presence expected)

Hours
Full Time

Salary
£325,000 - £485,000 GBP per annum

About the Role
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. Our team is a rapidly growing group of researchers, engineers, policy experts, and business leaders collaborating to build beneficial AI systems.

We operate some of the largest Kubernetes clusters in the industry, managing fleets of hundreds of thousands of nodes across multiple cloud providers and datacenters to train, research, and serve frontier AI models. The Kubernetes Platform team owns the Kubernetes control plane that powers these clusters.

At this scale, standard defaults no longer suffice. We own and extend the scheduler to place topology-sensitive ML workloads across thousands of accelerators simultaneously. We scale the control plane components—apiserver, etcd, controllers—to remain responsive as object and node counts grow exponentially. Additionally, we build core cluster services such as service discovery to ensure reliability under heavy load.

Your work will be critical in ensuring the control plane is fast, correct, and highly available, directly impacting Anthropic’s ability to safely and reliably train frontier AI models as our compute footprint expands.

Experience
- Significant software engineering experience building and operating production distributed systems
- Deep, hands-on Kubernetes experience beyond user-level, including scheduler, controllers, apiserver, or managing large multi-tenant clusters
- Proficiency in at least one systems programming language such as Go, Python, Rust, or C++
- Proven ability to debug complex issues across the stack, from API behavior to node and network-level root causes
- Track record designing systems for reliability, correctness, and clear failure semantics
- Strong written and verbal communication skills with experience building consensus among internal stakeholders

About You
- Comfortable leading large, ambiguous infrastructure projects with 12+ years of relevant industry experience
- Collaborative mindset with a passion for building scalable, reliable systems
- Motivated to work on cutting-edge AI infrastructure that has broad social and ethical implications

Qualifications
- Bachelor’s degree or equivalent combination of education, training, and/or experience in a relevant field
- Preferred experience includes:
- Contributions to Kubernetes internals (kube-scheduler, apiserver, etcd, client-go, controller-runtime)
- Experience with cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm)
- Background in scaling control planes or coordination systems (etcd, ZooKeeper, Consul)
- Familiarity with ML infrastructure: GPUs, TPUs, gang scheduling, topology-aware placement, collective networking (NCCL)
- Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code
- Low-level systems expertise such as Linux kernel tuning, cgroups, or eBPF

Additional Information
- Visa sponsorship available, with dedicated immigration support
- Hybrid work policy requiring minimum 25% office presence
- Anthropic values diversity and encourages applications from underrepresented groups
- Participation in on-call rotations, incident response leadership, and process design (postmortems, runbooks, SLOs) is expected