Sr. Manager, Engineering

xAI xAI · AI Frontier · Memphis, TN · Data Center

This role is for a Sr. Manager, Engineering to lead physical infrastructure engineering for xAI's hyperscale AI compute facilities. The role will oversee the design, development, and optimization of critical systems including structural, civil, architectural, controls, electrical, mechanical, HVAC, liquid cooling, power distribution, and fiber optic networks. The manager will build and lead a multidisciplinary engineering team, drive technical strategy, and ensure reliable, high-density, energy-efficient systems at scale.

What you'd actually do

  1. Lead the end-to-end engineering of physical infrastructure for xAI data centers and compute facilities, including structural and civil engineering (foundations, seismic design, site development, underground utilities), architectural engineering (facility layout, aesthetics, code compliance, and buildability), electrical systems (high-voltage, switchgear, UPS, generators, redundancy topologies), mechanical systems (HVAC, liquid cooling, chillers, CRAC/CRAH), controls & automation (BMS, SCADA, PLCs, monitoring), and high-capacity fiber optic networks (backbone, interconnects, and data hall connectivity).
  2. Build, mentor, and grow a high-performing multidisciplinary engineering team covering structural, civil, architectural, controls, electrical, mechanical, fiber infrastructure, and related disciplines.
  3. Develop and own technical standards, design guidelines, and best practices for power density, thermal management, structural integrity, seismic resilience, fiber performance and redundancy, uptime (targeting 99.999%+), efficiency (PUE/WUE optimization), and scalability to support massive GPU/accelerator clusters.
  4. Partner closely with construction, operations, AI hardware teams to ensure seamless integration from design through commissioning, startup, and handover.
  5. Drive innovation in areas such as advanced liquid cooling, high-efficiency power delivery, intelligent controls, sustainable materials and design, optimized facility layouts, and high-bandwidth, low-latency fiber infrastructure to meet the extreme demands of next-generation AI training.

Skills

Required

  • Bachelor’s degree in an engineering discipline
  • 7+ years of engineering experience
  • 2+ years in a direct people leadership role leading a team of engineers, contractors, technician or other support staff

Nice to have

  • 7+ years of experience in physical infrastructure engineering for data centers, hyperscaler facilities, power plants, or other industrial projects
  • Deep expertise across multiple disciplines: structural and civil engineering, architectural engineering, electrical (power distribution, substations, backup systems), mechanical (cooling, HVAC, fluid systems), controls/automation, and fiber optic infrastructure for mission-critical environments
  • Experience leading the design and delivery of high-density compute infrastructure supporting AI, HPC, or similar workloads at massive scale, including robust fiber networking
  • Strong track record of building and leading technical teams, delivering complex projects on aggressive schedules and budgets, and solving ambiguous, high-stakes engineering challenges
  • Hands-on experience with relevant tools and standards (e.g., AutoCAD, Revit, ETAP, BIM, structural analysis software, fiber design tools, ASHRAE, IEEE, NFPA, IBC, Uptime Institute Tier standards, TIA-942)
  • Ability to thrive in a high-velocity, high-ambiguity environment with a hands-on, continuous improvement mindset and exceptional problem-solving skills
  • Experience with liquid cooling systems, high-voltage power infrastructure for GPU clusters, advanced controls/BMS, large-scale structural/civil/architectural design, or high-capacity fiber networks for AI data centers
  • Background supporting hyperscalers, large AI training clusters, or similar power- and cooling-intensive environments with extensive fiber interconnects
  • Familiarity with fast-track design-build approaches, value engineering, sustainability practices, and integrated structural/architectural/fiber

What the JD emphasized

  • high-density compute infrastructure supporting AI, HPC, or similar workloads at massive scale, including robust fiber networking
  • building and leading technical teams, delivering complex projects on aggressive schedules and budgets, and solving ambiguous, high-stakes engineering challenges
  • liquid cooling systems, high-voltage power infrastructure for GPU clusters, advanced controls/BMS, large-scale structural/civil/architectural design, or high-capacity fiber networks for AI data centers
  • supporting hyperscalers, large AI training clusters, or similar power- and cooling-intensive environments with extensive fiber interconnects