Senior GPU Infrastructure Architect

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

Job summary

Prime Intellect in San Francisco is seeking a senior infrastructure engineer to design and deploy GPU-heavy workloads at scale. You will work directly with customers to translate workload requirements into robust GPU clusters and deployment strategies.

The role combines hands-on engineering with high-visibility architecture discussions, requiring deep knowledge of HPC tooling, networking, and production reliability.

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 workload requirements and design optimal GPU cluster architectures.
• Create technical proposals and capacity planning for clusters ranging 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 orchestration systems including SLURM and Kubernetes for distributed workloads.
• Implement high‑performance networking with InfiniBand, RoCE, and NVLink interconnects.
• Optimize GPU utilization, memory management, and inter‑node communication.
• Configure parallel filesystems (Lustre, BeeGFS, GPFS) for optimal I/O performance.
• Tune system performance from kernel parameters to CUDA configurations.
• Serve as primary technical escalation point for customer infrastructure issues.
• Diagnose and resolve complex problems across the full stack - hardware, drivers, networking, and software.
• Implement monitoring, alerting, and automated remediation systems.
• Provide 24/7 on‑call support for critical customer deployments.
• Create runbooks and documentation for customer operations teams.

Skills

GPU clusters and HPC environments

customer-facing technical leadership

Python

Bash

systems programming

CUDA ecosystem

driver stack

Tools

SLURM

Kubernetes

InfiniBand

NVIDIA CUDA

Docker

Containerd

Enroot

Terraform

Ansible

Job description

Prime Intellect in San Francisco is seeking a senior infrastructure engineer to design and deploy GPU-heavy workloads at scale. You will work directly with customers to translate workload requirements into robust GPU clusters and deployment strategies.

The role combines hands-on engineering with high-visibility architecture discussions, requiring deep knowledge of HPC tooling, networking, and production reliability.