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OpenAI's Industrial Compute team is seeking a senior Data Center Infrastructure Architect to design and optimize physical infrastructure for large-scale AI deployments. This is a hands-on technical role spanning data center architecture, electrical and mechanical systems, high-density compute, controls, telemetry, and digital modeling.
You will develop system-level architectures for high-density AI data centers across power, cooling, IT equipment, controls, and facility infrastructure. Key responsibilities include creating digital twins and computational models to represent data center system behavior under varying workloads and conditions, using design and operational data to identify constraints and improve efficiency metrics like PUE, and evaluating complex tradeoffs across electrical topology, cooling architecture, rack density, redundancy, and operational complexity.
You'll translate evolving AI hardware requirements into practical facility, rack, power, and thermal architectures, and establish reference architectures and modeling standards reusable across customer deployments. The role requires partnering across software, data, controls, hardware, mechanical, electrical, construction, commissioning, and operations teams to connect digital models with real infrastructure behavior.
Additional responsibilities include integrating telemetry from BMS, EPMS, DCIM, SCADA, and equipment controllers into modeling workflows, leading technical reviews of customer and partner designs with quantitative analysis, adapting reference solutions to site-specific constraints, and supporting pilots, commissioning, and post-deployment analysis to validate models and improve designs.
Required qualifications include significant experience designing or optimizing hyperscale data centers or comparable infrastructure systems, broad knowledge of data center electrical and mechanical systems, experience making system-level design decisions across multiple engineering disciplines, and proficiency with simulation, optimization, or digital-twin modeling techniques. You should have strong understanding of data center efficiency metrics, experience working with operational telemetry, ability to evaluate complex tradeoffs, and demonstrated leadership in ambiguous environments. A bachelor's degree in mechanical engineering, electrical engineering, systems engineering, applied physics, or related discipline is required.
Preferred experience includes high-density GPU clusters and direct-to-chip liquid cooling, connecting facility models with workload and thermal behavior, familiarity with modeling tools like Modelica, MATLAB/Simulink, Python, or EnergyPlus, experience with industrial controls systems, and a track record developing reference designs within hyperscalers or advanced engineering organizations.
