Kubernetes or Infrastructure Engineer

HPC — AWS Consultant

The Work The Cloud Foundation Team runs 15+ HPC clusters across AWS, CoreWeave, GCP, and other providers. 40,000+ GPUs today, supporting AI research and production training. We're scaling 10x in 2026.

This role is Kubernetes-heavy. You'll operate multi-cloud platform infrastructure where misconfigurations or failed upgrades translate directly into thousands of lost GPU-hours. The clusters are large enough that novel failure modes are routine.

Responsibilities

• Operate Kubernetes platforms (EKS, CKS, GKE) at significant scale across providers — cluster lifecycle, node pool management, networking policy, and maintaining stability during rapid growth.
• Provision HPC infrastructure through a CI/CD system (Conveyor) across AWS, CoreWeave, GCP, and OCI, with additional providers as you expand.
• Manage Slurm-based job scheduling to allocate GPU compute across training and inference workloads.
• Define and maintain SLIs/SLOs. Build monitoring and alerting.
• Participate in SEV response and author post-incident reviews.
• Coordinate daily with Networking, Storage, Security, and AI/ML platform teams.

Requirements

• 4+ years in infrastructure engineering, cloud platforms, or HPC.
• Kubernetes is the core requirement — hands-on experience operating clusters at meaningful scale: node pool sizing, scheduler debugging, CNI troubleshooting, and rolling upgrades across large fleets. Candidates whose K8s experience is limited to small or local environments are unlikely to be a fit.
• Terraform proficiency — you'll write and review infrastructure-as-code daily.
• Working knowledge of AWS (EC2, S3, EFS, FSx for Lustre).
• Python for tooling and automation.
• Slurm experience is a plus but not required.

Environment Remote-first. Occasional on-site visits to customer offices. Company laptop provided.