Kubernetes (K8S) / HPC Engineer

Capgemini • Atlanta, GA

3d • Remote

About The Position

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same. This role is remote in USA. As a Kubernetes (K8S) / HPC Engineer, you will be responsible for designing, deploying, and supporting scalable Kubernetes and High-Performance Computing (HPC) platforms that power AI/ML, simulation, and other compute-intensive workloads. You will work closely with platform engineering, data science, and research teams to deliver reliable, high-performance infrastructure across cloud and on-premises environments.

Requirements

• 5+ years of experience in Kubernetes, Cloud Infrastructure, Platform Engineering, DevOps, or related fields.
• Minimum 2+ years of experience supporting HPC or large-scale distributed compute environments.
• Strong hands-on experience with Kubernetes (K8S), Docker, Helm, and container orchestration technologies.
• Experience managing HPC clusters and workload schedulers, including Slurm and/or Volcano.
• Expertise with NVIDIA GPU infrastructure, GPU-enabled workloads, and performance optimization.
• Strong Linux administration and troubleshooting skills.
• Proficiency in Python and/or Bash scripting for automation and operational management.
• Experience implementing CI/CD pipelines, monitoring, logging, and infrastructure automation solutions.
• Hands-on experience with at least one major cloud platform, Azure AKS and Google Kubernetes Engine (GKE)
• Strong understanding of distributed systems, cloud-native architectures, scalability, and performance tuning.
• Excellent analytical, problem-solving, and cross-functional collaboration skills.

Nice To Haves

• Exposure to Trainium or Inferentia is highly preferred.

Responsibilities

• Design, deploy, and manage Kubernetes-based compute platforms for AI/ML and HPC workloads.
• Build and maintain scalable HPC environments utilizing workload schedulers.
• Support and optimize NVIDIA GPU infrastructure for machine learning, data processing, and simulation workloads.
• Implement infrastructure automation, CI/CD pipelines, and monitoring solutions to improve platform reliability and operational efficiency.
• Manage containerized applications using Kubernetes, Docker, and Helm.
• Troubleshoot and optimize cluster, network, storage, and application performance across distributed computing environments.
• Collaborate with engineering, research, and AI teams to enable high-performance computing and cloud-native solutions.
• Ensure platform scalability, availability, security, and operational excellence.

Benefits

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
• Company paid holidays
• Personal Days
• Sick Leave
• Medical, dental, and vision coverage
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed