Senior Manager, AI and HPC Cluster Engineering Enablement

Details

NVIDIA is reshaping accelerated computing and AI infrastructure through advancements in GPUs, networking, software, and large-scale datacenter platforms. The Applied Systems Engineering team is seeking a senior engineering manager to help internal engineers adopt next-generation AI/HPC clusters as they transition from initial setup to wider usage.

The role is responsible for cluster engineering support, growing the engineering community, creating hands-on training, and managing requests from engineering users and support teams. The manager will establish clear processes for request intake, prioritization, ownership, and communication, including onboarding, workload assistance, and access to experts for in-depth debugging.

The role partners with architecture, bringup, software, firmware, networking, storage, datacenter operations, performance, and program teams. The ideal candidate has engineering leadership and operational experience in Linux-based HPC/AI environments, along with the ability to develop people, manage competing requests, and translate technical knowledge into effective training and support.

Responsibilities

• Lead and grow a team dedicated to cluster engineering support, community involvement, training, and engineering request management.
• Develop an internal engineering community through onboarding, office hours, technical workshops, and knowledge sharing.
• Create training and documentation covering cluster access, workload submission, GPU resource scheduling, shared storage, operational procedures, and actionable support requests.
• Own request intake and prioritization by clarifying needs, capturing impact and priorities, identifying dependencies, and maintaining a transparent queue aligned with engineering achievements and available capacity.
• Coordinate requests requiring specialist investigation and deep-debug support by connecting requesters with technical owners, agreeing on next steps, tracking progress, and escalating stalled requests.
• Partner with cluster operations and engineering teams on access, allocations, maintenance communications, and resource needs.
• Convert recurring questions, request patterns, and specialist findings into reusable guidance, training, self-service tool proposals, and workflow improvements.
• Use request volume, response time, aging, completion trends, training participation, and user feedback to improve support quality and communicate priorities and capacity needs.

Requirements

• BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Science, or equivalent practical experience.
• At least 8 years of experience in high-performance computing, AI infrastructure, datacenter systems, production engineering, or large-scale Linux environments.
• At least 5 years of technical leadership or engineering management experience, including mentoring engineers, setting priorities, and delivering across organizational boundaries.
• Practical understanding of Linux clusters, GPU workload scheduling, cluster management, networking, servers, and large-scale shared storage.
• Experience coordinating engineering requests, support queues, or operational workflows, including prioritization, ownership, blocking issues, and communication through completion.
• Ability to translate complex infrastructure concepts into clear documentation, training, and guidance for engineers with different levels of experience.
• Strong collaboration and communication skills, with sound judgment when balancing user needs, engineering priorities, and resource constraints.

Preferred Qualifications

• Experience designing or operating large HPC/AI clusters and supporting engineers during early hardware, firmware, or software lifecycle phases.
• Experience with cluster management platforms, workload schedulers, GPU resource allocation, and large or petabyte-scale filesystems.
• Experience forming engineering communities, induction programs, technical workshops, or peer learning activities.
• Experience improving request workflows across compute, networking, storage, and software teams with clear handoffs, shared priorities, and measurable service improvements.
• Proven experience developing inclusive teams that foster ownership, knowledge transfer, thoughtful decision-making, and career growth.

Benefits

• Base salary range of $272,000–$431,250 for Level 4.
• Base salary range of $320,000–$488,750 for Level 5.
• Equity and benefits are included.