Resident Engineer – AI/GPU & Compute

We are seeking highly experienced Resident Engineers – AI/GPU & Compute to support a large-scale GPU as a Service (GPUaaS) initiative in KSA. This role requires deep technical expertise in AI infrastructure, high-performance computing (HPC), advanced networking, and enterprise virtualization environments. The selected candidates will provide on-site, hands-on operational support and expert-level troubleshooting within a mission-critical AI/GPU infrastructure environment.

Location: Riyadh, Saudi Arabia (On-site)

Work Conditions: Full-time, On-site

Key Responsibilities:

• Provide on-site day-to-day operational support for AI/GPU, compute, and networking environments.
• Support, operate, and optimize GPU as a Service (GPUaaS) infrastructure.
• Deliver expert-level troubleshooting across GPU clusters, compute platforms, and networking layers.
• Support and maintain High-Performance Computing (HPC) environments.
• Manage and support virtualization platforms and related infrastructure.
• Provide operational support for XE services and enterprise compute systems.
• Ensure system stability, performance optimization, and incident resolution.
• Perform root cause analysis (RCA) and implement preventive measures.
• Coordinate with customer technical teams and vendors for issue resolution.
• Conduct structured knowledge transfer sessions for customer engineering teams.
• Maintain documentation, operational runbooks, and best practices.

Required Technical Expertise:

• 8–12+ years of experience in enterprise infrastructure, data center operations, or resident engineering roles.
• Strong hands-on experience with:
  • AI / GPU platforms (NVIDIA or equivalent enterprise GPU environments)
  • High-Performance Computing (HPC) systems
  • Advanced networking for AI/GPU workloads
  • Virtualization technologies (VMware, Hyper-V, or similar)
  • XE services and enterprise compute environments
• Experience supporting large-scale, mission-critical infrastructure projects.
• Strong troubleshooting and performance optimization capabilities.
• Experience in GPU cluster deployment, scaling, and operational support is highly preferred.
• Ability to work in fast-paced, customer-facing, on-site environments.