Senior Manager, AI and HPC Cluster Engineering Enablement

This is a fully remote position, open to applicants in California, +4 more states.

📋 Description

• Lead and expand a team focused on cluster engineering support, community engagement, training, and the management of engineering requests.

• Cultivate an internal engineering community through onboarding programs, office hours, technical workshops, and knowledge dissemination.

• Develop comprehensive training materials and documentation for cluster access, workload submission, GPU resource scheduling, shared storage, operational procedures, and actionable support requests.

• Manage request intake and prioritization by clarifying needs, assessing impact and priorities, identifying dependencies, and maintaining a transparent queue.

• Coordinate detailed investigations and deep-debug support, connect requesters with technical leads, monitor progress, and resolve stalled requests.

• Collaborate with cluster operations and engineering teams regarding access, allocations, maintenance communications, and resource requirements.

• Transform recurring inquiries, request patterns, and specialist insights into reusable guidance, training materials, self-service tools, and workflow enhancements.

• Utilize metrics such as request volume, response times, aging, completion trends, training participation, and user feedback to enhance support quality and communicate priorities and capacity needs.

⛳️ Requirements

• Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Science, or relevant practical experience.

• Over 8 years of experience in high-performance computing, AI infrastructure, datacenter systems, production engineering, or extensive Linux environments.

• At least 5 years of technical leadership or engineering management experience, including mentoring engineers, establishing priorities, and delivering results across organizational boundaries.

• Solid understanding of Linux clusters, GPU workload scheduling, cluster management, networking, servers, and large-scale shared storage systems.

• Experience coordinating engineering requests, managing support queues, or operational workflows, including prioritization, ownership, handling blocking issues, and communication until completion.

• Ability to simplify complex infrastructure concepts into clear documentation, training, and guidance.

• Excellent collaboration and communication skills, with sound judgment in balancing user needs, engineering priorities, and resource limitations.

• Experience in designing or operating large HPC/AI clusters and supporting engineers during the early phases of hardware, firmware, or software lifecycles.

• Familiarity with cluster management platforms, workload schedulers, GPU resource allocation, and large or petabyte-scale filesystems.

• Proven experience in establishing engineering communities, induction programs, technical workshops, or peer learning initiatives.

• Experience enhancing request workflows across compute, networking, storage, and software teams.

• Demonstrated success in developing inclusive teams that promote ownership, knowledge transfer, thoughtful decision-making, and career advancement.

🏝️ Benefits

• Equity

• Benefits