*Note: This position requires presence in our San Jose office location 4 days per week; Lambda's designated work from home day is currently Tuesday.
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.
What You'll Do- 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.
You- 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)
Nice to Have- Experience in the machine learning / AI infrastructure / GPU / HPC / computer hardware industry
- Exposure to data center standards, certifications (e.g. ISO, Uptime Institute, etc.)
- Experience working on vendor quality, supply chain quality, or incoming inspections
- Understanding of firmware, embedded systems, reliability engineering
- Familiarity with scripting or automation (Python, SQL, etc.) to help with data processing
- Exposure to cloud or hyperscaler infrastructure operations
- Experience with "manufacturing-like" quality concepts applied to compute hardware
Salary Range InformationThe annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
