Senior GPU Infrastructure Engineer — HPC & Clusters

Prime Intellect AI; San Francisco (CA); On-site; USD 150,000 - 300,000; Full time

Job summary

Prime Intellect AI in San Francisco seeks an experienced engineer to design GPU cluster architectures, deploy strategies for LLM training and HPC workloads, and present architectural recommendations to clients.

You will deploy orchestration with SLURM and Kubernetes, optimize interconnects, and provide 24/7 on‑call support for critical deployments, collaborating with top engineering teams to push frontier AI infrastructure.

Qualifications

• 3+ years hands-on experience with GPU clusters and HPC environments.
• Deep expertise with SLURM and Kubernetes in production GPU settings.
• Proven experience with InfiniBand configuration and troubleshooting.
• Strong understanding of NVIDIA GPU architecture, CUDA ecosystem, and driver stack.
• Experience with infrastructure automation tools (Ansible, Terraform).
• Proficiency in Python, Bash, and systems programming.
• Track record of customer-facing technical leadership.

Responsibilities

• Partner with clients to understand workloads and design GPU cluster architectures.
• Create proposals and capacity plans for clusters from 100 to 10,000+ GPUs.
• Develop deployment strategies for LLM training, inference, and HPC workloads.
• Present architectural recommendations to technical and executive stakeholders.
• Deploy and configure SLURM and Kubernetes for distributed workloads.
• Implement high-performance networking and optimize GPU utilization.
• Provide 24/7 on-call support for critical deployments.
• Create runbooks and documentation for operations teams.
• Diagnose and resolve complex hardware, drivers, networking, and software problems.

Skills

GPU clusters

HPC environments

SLURM

Kubernetes

NVIDIA CUDA

Python

Bash

Customer-facing leadership

Tools

Ansible

Terraform

Docker

Containerd

Job description

Prime Intellect AI in San Francisco seeks an experienced engineer to design GPU cluster architectures, deploy strategies for LLM training and HPC workloads, and present architectural recommendations to clients.

You will deploy orchestration with SLURM and Kubernetes, optimize interconnects, and provide 24/7 on‑call support for critical deployments, collaborating with top engineering teams to push frontier AI infrastructure.