Controls Engineer (Supercomputer Infrastructure)

Location: Onsite in the Memphis, Tennessee / Southaven, Mississippi area, with work across the Memphis / Southaven campus

Company

xAI develops AI systems designed to understand the universe and support humanity's pursuit of knowledge.

What you will do

• Design, build, and activate control systems for AI training campuses and critical physical infrastructure.
• Develop and commission automation for cooling plants, electrical distribution, liquid-cooling loops, and data halls.
• Lay out NFPA 79/NEC/UL508A-compliant control panels and create electrical, pneumatic, and fluid schematics.
• Architect, write, debug, document, and maintain PLC code, HMI screens, BMS, EPMS, and SCADA systems.
• Manage electrical cabinet builds, field wiring, pneumatic and fluid plumbing, and component selection.
• Set and maintain project schedules and budgets while deploying systems into live campus operations.

Requirements

• Bachelor's degree in an engineering discipline.
• At least 1 year of professional experience designing and commissioning industrial automation and controls systems.
• Ability to work onsite in the Memphis, Tennessee / Southaven, Mississippi area.
• Willingness to work extended hours and weekends as needed.
• Willingness to travel to other locations.
• Strong written and verbal communication skills and the ability to solve complex problems independently or within an integrated team.

Nice to have

• Experience with PLC programming, preferably Siemens TIA Portal and Beckhoff TwinCAT 3.
• HMI and SCADA programming experience, preferably with Ignition.
• Experience with C#, .NET, Python, SQL, EPlan, Delta controls, and industrial communication networks.
• Knowledge of NEC, NFPA 79, and UL508A codes, plus experience with control panels and electromechanical systems.
• Experience in data centers, power generation, semiconductor, or other high-reliability industrial environments.

Culture & Benefits

• Work in a small, highly motivated organization focused on engineering excellence.
• Contribute directly through a hands-on, flat organizational structure.
• Work on technically advanced AI training campuses and critical infrastructure systems.
• Operate in a fast-paced, iterative design and commissioning environment.