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# Infrastructure Engineer (Kubernetes, GPU/NVIDIA, Terraform)

- **Company:** ITcaps LLC
- **Location:** St. Louis, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Ubuntu (Operating System), Nvidia CUDA, Linux, DevOps, Prometheus, Azure Machine Learning, Runbook, AI Infrastructure, Ceph (Software), Graphics Processing Unit (GPU), Cloud Platform System, Grafana, Software Troubleshooting, Kubernetes, Infrastructure Automation Frameworks, Hardware Infrastructure, Terraform
- **Published:** August 6, 2026
- **Apply:** https://www.dice.com/job-detail/4acbfeac-1671-4c19-9006-dbdb683a71fb

## About the Role

We are seeking a highly skilled AI Infrastructure Engineer to design, build, and support scalable GPU-enabled Kubernetes platforms for AI/ML workloads. The ideal candidate will have strong expertise in Kubernetes, Linux, Terraform, and NVIDIA GPU technologies, with experience building enterprise-grade AI infrastructure., * Strong hands-on experience with Kubernetes

 * Expertise in Linux (Ubuntu)
 * Experience with Terraform (Infrastructure as Code)
 * Experience with GPUs and NVIDIA Stack (CUDA, NVIDIA GPU Operator, device plugins, scheduling)
 * Strong troubleshooting and automation skills

Preferred Skills

 * Experience with Longhorn or Ceph storage
 * Knowledge of Canonical ecosystem (MAAS, Juju, Charmed Kubernetes)
 * Experience with Kubeflow or other AI/ML platform tools
 * Certifications such as CKA or NVIDIA Certified, * Kubernetes
 * Linux (Ubuntu)
 * Terraform
 * NVIDIA GPU Stack
 * GPU Infrastructure
 * Prometheus
 * Grafana
 * AI Infrastructure
 * Infrastructure Automation, * Longhorn
 * Ceph
 * Kubeflow
 * MAAS
 * Juju
 * Charmed Kubernetes
 * CKA Certification
 * NVIDIA Certification

## Description

* Design, deploy, and manage production-grade Kubernetes clusters
 * Build and maintain GPU-enabled infrastructure for AI/ML workloads
 * Deploy and manage Longhorn storage solutions
 * Automate infrastructure provisioning using Terraform
 * Monitor and optimize platform performance using Prometheus and Grafana
 * Troubleshoot Kubernetes, GPU, storage, and infrastructure issues
 * Collaborate with ML engineers, data scientists, and DevOps teams
 * Create technical documentation, runbooks, and operational guides
 * Conduct knowledge transfer (KT) sessions and hands-on workshops for client teams
 * Provide guidance on Kubernetes operations, NVIDIA GPU management, Longhorn storage, and Canonical ecosystem tools
 * Advise on cloud-native infrastructure, AI/ML platform best practices, scalability, reliability, and cost optimization
 * Ensure successful production handoff with full operational readiness


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