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.