Federal GPU Infrastructure Architect

NVIDIA Gruppe; Austin (TX); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking an Infrastructure Solutions Architect to support OEM Federal deployments of GPU-accelerated platforms. You will own issues end to end, perform failure analysis, and ensure hardware returns meet security requirements in FedRAMP/IL5/IL6 environments.

This role requires up to 35% travel and a strong background in multi-GPU systems. Ideal candidates have 5+ years in engineering on multi-GPU platforms, Linux optimization for AI workloads, and excellent communication skills for

Qualifications

• BS or MS in Computer Engineering, Electrical Engineering, Computer Science, or equivalent experience.
• 5+ years of engineering experience on multi-GPU platforms, including customer-facing roles.
• Strong system software expertise across firmware, BIOS, kernel, drivers, and Linux for AI/ML workloads.

Responsibilities

• Serve as senior technical contact for OEM Federal deployments of NVIDIA GPU platforms.
• Own issues end to end, drive logs and reproduction details to engineering, ensure resolution.
• Perform failure analysis and RMA procedures for Federal deployments, including on-site cases when needed.
• Navigate Federal security frameworks (FedRAMP, IL5/IL6, SCIF) and ensure sanitization and chain-of-custody for hardware returns.
• Collaborate with OEM Federal support to reduce blocking issues and build a Federal knowledge base.

Skills

Python

C/C++

Docker

Kubernetes

NCCL/MPI

Linux

Education

BS/MS in CS/EE/CE

Tools

Dell PowerEdge GPUs

OpenManage/APEX

Job description

NVIDIA is seeking an Infrastructure Solutions Architect to support OEM Federal deployments of GPU-accelerated platforms. You will own issues end to end, perform failure analysis, and ensure hardware returns meet security requirements in FedRAMP/IL5/IL6 environments.

This role requires up to 35% travel and a strong background in multi-GPU systems. Ideal candidates have 5+ years in engineering on multi-GPU platforms, Linux optimization for AI workloads, and excellent communication skills for