Infrastructure Engineer

ITCAPS LLC; St. Louis (MO); On-site; USD 140,000 - 200,000; Full time

Job summary

ITCAPS LLC in St. Louis, MO is seeking an AI Infrastructure Engineer to design, build, and operate scalable GPU-enabled Kubernetes platforms for AI/ML workloads. You will shape the on-prem and cloud-native infrastructure to support advanced analytics and model deployment.

The role requires hands-on experience with Kubernetes, Linux (Ubuntu), NVIDIA stacks, and Terraform, plus a passion for automation, reliability, and cost optimization in AI environments.

Qualifications

• Experience in designing and managing GPU-enabled Kubernetes clusters.
• Strong Linux (Ubuntu) expertise.
• Proficient with NVIDIA GPUs and stack.
• Hands-on with Terraform and IaC.
• Experience with GPU AI/ML workloads.

Responsibilities

• Design and manage Kubernetes clusters.
• Build and manage GPU-enabled infrastructure.
• Deploy and manage Longhorn storage.
• Automate infrastructure using Terraform.
• Monitor platforms with Prometheus and Grafana.
• Troubleshoot and optimize AI/ML infrastructure.

Skills

Kubernetes

Linux/Ubuntu

NVIDIA stack

Terraform

GPU infrastructure

Tools

Longhorn

Ceph

MAAS/Juju/Charmed Kubernetes

Kubeflow

Prometheus

Grafana

Job description

Role Overview:

Seeking a highly skilled AI Infrastructure Engineer to design, build, and operate scalable GPU-enabled Kubernetes platforms for AI/ML workloads.

Must-Have Skills

• Strong Kubernetes experience
• Linux/Ubuntu expertise
• NVIDIA GPUs and NVIDIA stack
• Terraform
• GPU-enabled Kubernetes infrastructure

Responsibilities

• Design and manage Kubernetes clusters
• Build and manage GPU-enabled infrastructure
• Deploy and manage Longhorn storage
• Automate infrastructure using Terraform
• Monitor platforms using Prometheus and Grafana
• Troubleshoot and optimize AI/ML infrastructure

Preferred Skills

• Longhorn or Ceph
• Canonical MAAS, Juju, or Charmed Kubernetes
• Kubeflow or other AI/ML platforms
• CKA or NVIDIA certifications

Knowledge Transfer & Client Enablement

• Conduct KT sessions on Kubernetes, GPU infrastructure, NVIDIA stack, and storage
• Create technical documentation, runbooks, and training materials
• Conduct hands-on workshops for client teams
• Advise on cloud-native infrastructure, AI/ML operations, reliability, performance, and cost optimization
• Ensure smooth production handoff and operational readiness

Soft Skills

• Strong troubleshooting and problem-solving
• Excellent communication and documentation
• Ability to collaborate with ML engineers and data scientists
• Strong focus on automation and platform scalability