Data Center Operations Engineer

Data Center Operations Engineer — Key Requirements

Location: Dallas–Fort Worth, USA (on-site)

Role Overview

Hands-on role responsible for operating and maintaining high-performance computing (HPC) and AI infrastructure, with a particular focus on GPU-based systems. The priority is keeping GPU hardware running reliably, resolving failures quickly, and deploying new equipment.

Key Responsibilities

• Install, maintain, and troubleshoot NVIDIA GPU servers and HPC infrastructure.
• Diagnose hardware failures and respond to monitoring alerts to minimize downtime.
• Perform firmware updates, component replacements, and hardware repairs.
• Support high-performance networking and storage connected to GPU compute systems.
• Manage hardware assets, spare parts, vendor support, and RMAs.
• Support new hardware deployments and data center expansions.
• Investigate incidents, identify root causes, and improve monitoring and automation.
• Participate in a 24/7 on-call rotation.
• Travel across North America to support new data center deployments.

Required Experience

• 3+ years of experience in data center operations, hardware engineering, or HPC infrastructure.
• Hands-on experience with NVIDIA GPU servers or equivalent high-performance computing systems.
• Strong server hardware troubleshooting skills, including firmware management and component replacement.
• Experience with high-performance networking and storage.
• Understanding of HPC and AI workloads.
• Experience maintaining hardware availability in a production environment.

Preferred Experience

• Experience with NVIDIA HGX systems.
• Supermicro or Dell HGX hardware certifications or training.
• Experience with greenfield data center deployments.
• Knowledge of cooling, power distribution, and data center infrastructure.
• Networking or hardware certifications; ITIL knowledge.

Ideal Candidate

A technically strong, hands-on hardware engineer with genuine GPU infrastructure experience who can troubleshoot complex failures, maintain uptime, and support the deployment of large-scale AI infrastructure.