Senior Hardware Quality Engineer

This role is responsible for end‑to‑end hardware quality engineering for large‑scale AI and GPU‑based data center fleets, with a focus on early failure detection, root cause analysis, and operational quality enablement. The position partners closely with data center operations, firmware, platform engineering, diagnostics, and vendor teams to improve hardware reliability, reduce repeat incidents, and accelerate mean‑time‑to‑resolution (MTTR) across production AI infrastructure. The scope and depth of this role reflect workload and technical responsibilities performed by a Senior Hardware Quality Engineer working with data centers, including debugging, telemetry analysis, diagnostics workflow design, and quality process ownership across GPU, power, storage, and platform subsystems. Lead deep‑dive investigations into complex hardware failures across AI/GPU platforms, including no-boot, GPU throttling, power delivery issues, and BMC related issues. Perform single‑node and rack‑level validation to confirm hardware remediation effectiveness before fleet re‑entry. Analyze large volumes of hardware telemetry, logs, and diagnostics data to identify systemic failure patterns and repeat offenders. Define and drive lightweight diagnostics and telemetry workflows that allow technicians and operations teams to validate repairs before ticket closure, reducing repeat failures and rework. Partner with diagnostics and platform teams to enable out‑of‑band telemetry collection (e.g., BMC SEL, PCIe health indicators), integrate diagnostics into existing operational tools and workflows. Own fleet‑level quality assessments for AI and GPU deployments, including early deployment phases and ongoing production monitoring. Drive improvements to Failure detection latency, root cause attribution accuracy and preventative quality controls (left‑shifting detection into earlier lifecycle stages). Sync with Firmware and electrical engineering teams on corrective actions (e.g., CPLD firmware changes, power quality investigations). Collaborate with supply chain and spares teams to ensure hardware availability aligns with failure remediation needs. Ability to work with Data center operations leadership to ensure solutions scale globally and align with operational SLAs. Produce and maintain technical documentation, failure mode analyses (FMEA), and quality playbooks for sustained operational excellence. Doctorate Degree in Mechanical Engineering, Materials Engineering, Reliability Engineering, Electrical Engineering, or related field AND 2+ years technical engineering experience OR Master's Degree in Mechanical Engineering, Materials Engineering, Reliability Engineering, Electrical Engineering, or related field AND 4+ years technical engineering experience OR Bachelor's Degree in Mechanical Engineering, Materials Engineering, Reliability Engineering, Electrical Engineering, or related field AND 5+ years technical engineering experience OR 12+ years relevant technical engineering experience Doctorate Degree in Mechanical Engineering, Materials Engineering, Reliability Engineering, Electrical Engineering, Systems Engineering, or related field AND 4+ years technical engineering experience OR Master's Degree in Mechanical Engineering, Materials Engineering, Reliability Engineering, Electrical Engineering, Systems Engineering , or related field AND 7+ years technical engineering experience OR Bachelor's Degree in Mechanical Engineering, Materials Engineering, Reliability Engineering, Electrical Engineering, Systems Engineering, or related field AND 9+ years technical engineering experience. Leadership skills and ability to collaborate with diverse teams and drive a call to action. 10+ years of experience in working with the modern server architectures and/or their subsystems - including GPU, CPU, AI hardware, Memory and methods for root cause analysis and debugging. Project management skills.