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# DevOps Specialist

- **Company:** Capgemini
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $77,730.0 - $121,451.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Bash Shell, Cloud Computing, Cloud Foundry, Continuous Integration, DevOps, Distributed Systems, Monitoring of Systems, InfiniBand, Python (Programming Language), Linux System Administration, Machine Learning, Performance Tuning, Remote Direct Memory Access, Scientific Computating, Scripting, Graphics Processing Unit (GPU), Cloud Platform System, High Performance Computing, Containerization, Kubernetes, Infrastructure Automation Frameworks, Storage Technologies, Slurm, Machine Learning Operations, Hardware Infrastructure, Docker
- **Published:** October 6, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=9901e12e7459c75c

## About the Role

* 5+ years of experience in Kubernetes and cloud infrastructure engineering.
 * 2+ years of experience supporting HPC or large-scale compute platforms.
 * Strong Linux administration experience.
 * Experience with Kubernetes, Docker, Helm, and container orchestration.
 * Experience with Python and/or Bash scripting.
 * Experience supporting Azure, AWS, or GCP environments.

Required Technical Skills:

 * Kubernetes (K8S)
 * Docker
 * Helm
 * Linux Administration
 * Python
 * Bash
 * HPC Clusters
 * Slurm and/or Volcano
 * NVIDIA GPU Infrastructure
 * CI/CD
 * Infrastructure Automation
 * Monitoring & Observability
 * AKS, EKS, and/or GKE, * Experience with RDMA and/or InfiniBand.
 * Experience with parallel storage systems and large-scale compute environments.
 * Experience supporting AI model training, semiconductor workloads, scientific computing, or engineering simulations.

Must Haves:

 * Hands-on Kubernetes administration experience including Docker and Helm.
 * Experience supporting HPC environments utilizing Slurm, Volcano, or similar workload schedulers.
 * Strong Linux administration, scripting, and infrastructure automation expertise.

Nice to Haves:

 * Experience with NVIDIA GPU infrastructure and AI/ML workloads.
 * Experience with AKS, EKS, or GKE.
 * Experience with RDMA, InfiniBand, or parallel storage technologies.

## Description

linux
cloud infrastructure
hpc
slurm
GPU Infrastructure
kubernetes, We are seeking an experienced Kubernetes (K8S) & High-Performance Computing (HPC) Engineer to design, deploy, and support scalable compute platforms for AI/ML, simulation, and data-intensive workloads. This role will focus on Kubernetes administration, containerized infrastructure, HPC environments, GPU-enabled computing, and cloud-native platform engineering., * Design, deploy, and manage Kubernetes-based compute platforms supporting AI/ML, simulation, and high-performance workloads.

 * Implement and support containerized environments using Kubernetes, Docker, and Helm.
 * Administer and optimize HPC clusters, workload schedulers, and distributed computing environments.
 * Support GPU infrastructure and performance tuning for compute-intensive workloads.
 * Develop and maintain infrastructure automation, monitoring, and CI/CD pipelines.
 * Deploy and support cloud-native infrastructure across AKS, EKS, and/or GKE environments.
 * Troubleshoot platform performance, scalability, and availability issues.