> Markdown version of [/jobs/ext/3851810-remote-ai-infrastructure-systems-engineer](https://www.wearedevelopers.com/jobs/ext/3851810-remote-ai-infrastructure-systems-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # REMOTE AI Infrastructure Systems Engineer - **Company:** Insight Global - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computing Platforms, Systems Engineering, Data Centers, Distributed Systems, Ethernet, Hardware Design, InfiniBand, Linux System Administration, Performance Tuning, Software Engineering, AI Infrastructure, High Performance Computing, Computer Network Technologies, Containerization, AI Platforms, Kubernetes, Slurm - **Published:** October 21, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3462161009&tx=KK303PFK&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role 5+ years of experience in data center infrastructure, HPC, AI infrastructure, or systems engineering. Hands-on experience deploying or supporting NVIDIA GB200, GB300, DGX, HGX, or similar GPU-based computing platforms. Strong experience with NVIDIA networking technologies, including InfiniBand and high-speed Ethernet fabrics. Experience supporting hyperscale, AI, HPC, or mission-critical data center environments. Knowledge of rack-level deployment, server provisioning, and hardware integration. Experience configuring and troubleshooting Linux-based systems. Understanding of GPU cluster architecture, distributed computing environments, and AI infrastructure operations. **Ability to travel once hired for onboarding/ramp up. Remote past that! Experience with NVIDIA Mission Control, Base Command, or DGX ecosystem technologies. Experience deploying liquid-cooled infrastructure and high-density compute environments. Familiarity with Kubernetes, Slurm, containerized workloads, and cluster orchestration. ## Description We are seeking a highly skilled AI Infrastructure Systems Engineer to lead the deployment, provisioning, and optimization of next-generation NVIDIA GB300 NVL72 AI supercomputer clusters. This role sits at the intersection of data center infrastructure, high-performance networking, and AI platform operations. The ideal candidate will be responsible for bringing up liquid-cooled compute environments, configuring NVIDIA networking solutions, and establishing scalable management and orchestration frameworks to support large-scale AI workloads. This is an opportunity to work directly with cutting-edge Blackwell Ultra AI infrastructure, enabling advanced AI training and reasoning environments at hyperscale. Responsibilities * Deploy and provision NVIDIA GB300 NVL72 AI infrastructure within enterprise and hyperscale data center environments. * Configure and validate NVIDIA networking technologies, including high-bandwidth Ethernet and InfiniBand fabrics. * Bring online and optimize liquid-cooled compute trays, racks, and supporting infrastructure. * Deploy, configure, and manage NVIDIA Mission Control environments. * Support cluster integration, system bring-up, validation, testing, and performance tuning. * Collaborate with data center, networking, platform engineering, and operations teams to ensure infrastructure readiness. * Troubleshoot hardware, networking, storage, and software issues impacting AI cluster performance. * Develop automation and operational procedures for cluster deployment, monitoring, and lifecycle management. * Ensure system stability, reliability, and scalability across AI compute environments. * Support customer-facing deployments and provide technical leadership throughout implementation efforts.