AI Infrastructure Systems Engineer

Company: Insight Global

Title: AI Infrastructure Systems Engineer

Location: Remote | Santa Clara, CA worksite | Initial onboarding/ramp-up travel required

Duration: 12 month contract

Job Description

Insight Global is seeking an AI Infrastructure Systems Engineer to support the deployment and optimization of next-generation NVIDIA GB300 NVL72 AI supercomputer infrastructure .

This is a highly technical role focused on bringing large-scale GPU clusters online, integrating high-performance networking, commissioning liquid-cooled infrastructure, and building reliable operating environments for advanced AI workloads.

The engineer will work across GPU compute, Linux systems, InfiniBand/Ethernet networking, data center infrastructure, and cluster operations. This is an excellent opportunity for an engineer with deep NVIDIA, HPC, or AI infrastructure experience to work directly with Blackwell Ultra-class infrastructure .

Responsibilities:

• Deploy and provision NVIDIA GB300 NVL72 AI infrastructure.
• Configure and validate high-performance InfiniBand and Ethernet fabrics .
• Bring online liquid-cooled compute trays, racks, and related infrastructure.
• Deploy and manage NVIDIA Mission Control environments.
• Perform cluster bring-up, integration, validation, testing, and performance tuning.
• Troubleshoot GPU hardware, Linux, storage, networking, and software issues.
• Partner with networking, data center, platform, and operations engineering teams.
• Automate cluster deployment, monitoring, and lifecycle-management activities.
• Maintain infrastructure reliability, scalability, and performance.
• Provide hands-on technical leadership during customer-facing deployments.

Qualifications

• 5+ years of experience with data center infrastructure, HPC, AI infrastructure, or systems engineering.
• Hands-on experience with NVIDIA GB200, GB300, DGX, HGX , or similar GPU platforms.
• Strong expertise with InfiniBand and high-speed Ethernet networking .
• Experience supporting enterprise, hyperscale, HPC, AI, or mission-critical data center environments.
• Experience with rack-level deployments, server provisioning, system bring-up, and hardware integration.
• Strong Linux configuration and troubleshooting experience.
• Solid understanding of GPU clusters and distributed computing architectures.
• Ability to travel for initial onboarding/ramp-up before transitioning to remote work.

Preferred:

• NVIDIA Mission Control, Base Command, or DGX ecosystem experience.
• Liquid-cooling and high-density compute experience.
• Kubernetes, Slurm, containers, or cluster orchestration experience.