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.