Data Center Hardware Quality & Reliability Engineer

About The Role Own the end-to-end data-center hardware quality and reliability loop for OpenAI's 3P infrastructure and 1P current and next-gen platforms. Turn field failures into quantified risk, fast containment, verified root cause, improved MQE/NPI and manufacturing-test coverage, accurate spares forecasts, and upstream changes that prevent recurrence. The first hire must combine practical hardware/system understanding, reliability engineering, data fluency, and cross-functional technical leadership at data-center scale.

• Build and govern the field-quality data model across telemetry, tickets, RMA/repair, FA, firmware, configuration, supplier, and manufacturing genealogy.
• Define AFR, ASR, DPPM, MTBF/MTTR, repeat-repair, NTF, repair-cycle-time, and forecast-versus-actual metrics with explicit denominators and uncertainty.
• Provide fleet-level macro views and unit/FRU/cohort-level micro views; detect shifts and bound affected populations.
• Lead systemic field-failure triage, containment, failure analysis, 8D/CAPA, risk assessment, corrective-action verification, and recurrence monitoring.
• Develop cohort, life-data, reliability-growth, and spare-demand projections by product, FRU, supplier, configuration, geography, and age.
• Partner with MQE and NPI to convert field mechanisms into manufacturing-test coverage, screening/stress profiles, diagnostics, control plans, DFR/DFS requirements, FMEA/FTA, mission profiles, FRU strategy, and qualification gates.
• Close the loop by verifying whether upstream changes reduce field recurrence.
• Define supplier/CM FA standards, field-data contracts, scorecards, escalation paths, and closure evidence.
• Provide serviceability, TCO, and spares inputs without owning inventory execution or procurement.
• Create concise executive decision packages: population at risk, exposure, confidence, options, cost/risk, and recommendation.
• Run the cross-functional reliability council and, as the team grows, mentor