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Lead Platform Engineer/Architect - HPC, Kubernetes

EPAM Systems

Job
30950
Posted
Location
Remote
Work type
Full Time
Tax terms
W2, Yearly
Experience
Experience open
Openings
1 opening

Skills

  • HPC
  • Kubernetes
  • Lifecycle Management
  • ProVision
  • Continuous Integration
  • Continuous Delivery
  • Google Cloud
  • Google Cloud Platform
  • OCI
  • Job Scheduling
  • GPU
  • Computer Networking
  • Artificial Intelligence
  • Machine Learning (ML)
  • Cloud Computing
  • High Performance Computing
  • Debugging
  • Python
  • Scripting
  • Rust

About the job

Join a high-growth infrastructure team operating Kubernetes platforms across multiple cloud providers at massive scale. You'll build the systems that power thousands of GPUs, where your code and configurations directly protect thousands of GPU-hours from costly failures. EPAM is where tech talent thrives-building groundbreaking solutions, advancing your skills through world-class learning platforms, and working alongside a global community of problem-solvers to make the future real. Req# Responsibilities Operate and scale Kubernetes platforms (EKS, GKE, and other distributions) including cluster lifecycle management, node pool optimization, and networking policies during periods of rapid growth Provision and manage HPC infrastructure through CI/CD pipelines spanning AWS, CoreWeave, Google Cloud Platform, OCI, and additional cloud providers Design and maintain job scheduling systems that efficiently allocate GPU compute resources across training and inference workloads Define SLIs/SLOs, build robust monitoring and alerting systems, and actively participate in incident response and post-incident reviews Develop production-quality tooling and automation to support multi-cloud infrastructure operations at scale Collaborate daily with Networking, Storage, Security, and AI/ML platform teams to ensure seamless cross-functional infrastructure delivery Requirements 10+ years of experience in infrastructure engineering, cloud platforms, or high-performance computing environments Expert-level Kubernetes experience at meaningful scale, including node pool sizing, scheduler debugging, CNI troubleshooting, and rolling upgrades across large fleets Advanced Python skills with a track record of building production-grade tools, not just scripts; experience with Go, Rust, or C++ is a strong plus Daily proficiency in Terraform for writing and reviewing infrastructure as code Working knowledge of core AWS services including EC2, S3, EFS, and FSx for Lustre Strong site reliability engineering background with experience building monitoring, alerting, and incident response practices CKA, CKS certificates are highly preferred

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