Hardware Quality Engineer, Lambda

• Have experience working with hardware / data center / infrastructure systems
• Are strong at data analysis, statistics, and metrics (you can turn raw data into insight)
• Are skilled in root cause analysis methods (5 Whys, fishbone, 8D, A3, etc.)
• Are comfortable managing cross-team communication, stakeholder expectations, and conflict resolution
• Are detail-oriented, process-driven, and quality-minded
• Have experience working with quality tools or QMS software (e.g. audit modules, ERP, defect tracking)
• Communicate clearly in English (both written and verbal)
• Strong understanding of Linux systems — able to troubleshoot, analyze logs, and debug hardware/software interactions
• Hands-on experience working with server or data center hardware (GPUs, CPUs, NICs, DIMMs, power and cooling systems) and GPU clusters, InfiniBand, and RoCE-based interconnects
• Familiarity with root cause analysis (RCA) and Corrective & Preventive Actions (CAPA) processes
• Experience managing and tracking hardware failures, RMAs, and quality issues using tools or QMS platforms.(e.g. audit modules, ERP, defect tracking)
• Ability to write and maintain simple scripts (Python, Bash, or SQL) for data collection, analysis, and automation
• Strong analytical skills: comfortable using data to identify trends, anomalies, and reliability issues
• Detail-oriented and process-driven mindset; able to document findings and follow through on corrective actions
• Excellent communication skills: clear in writing and speaking, able to work across technical and non-technical teams
• Willingness to travel to data centers (up to ~30%) for audits, inspections, and troubleshooting
• 3+ years of experience in hardware quality engineering, reliability, or RMA operations within hyperscale or HPC environments

Desirable

• The Operations team plays a critical role in ensuring the seamless end-to-end execution of our AI-IaaS infrastructure and hardware
• This team is responsible for sourcing all necessary infrastructure and components, overseeing day-to-day data center operations to maintain optimal performance and uptime, and driving cross company coordination through product management organization to align operational capabilities with strategic goals
• By managing the full lifecycle from procurement to deployment and operational efficiency, the Operations team ensures that our AI-driven infrastructure is reliable, scalable, and aligned with business priorities
• Track, log, and manage all quality issues arising in the data center during deployment and production environment
• Perform root cause analysis (RCA) for every failure (hardware, software, process)
• Analyze production system metrics and quality data to detect trends, anomalies, or weak points
• Improve turnaround time (TAT) for Return Merchandise Authorization (RMA) processes
• Design, monitor, and drive corrective and preventive actions (CAPA)
• Implement and verify containment actions to keep systems operational until permanent fixes are applied
• Collaborate with operations, hardware, engineering, supply chain, and vendors to resolve quality issues
• Capture and upload failure analysis (FA) reports and related data into Quality Management Systems (QMS)
• Verify quality of spares (incoming and outgoing) to avoid repeat failures
• Define and track quality KPIs / SLAs and report on quality performance to leadership
• Oversee MRB (Material Review Board) inventory, rework, disposal decisions
• Ensure the quality management system (QMS) is up to date, with necessary training rolled out
• Work cross-functionally during hardware ramp, deployments, and upgrades to ensure quality gates
• Up to 30% travel may be required for this role