Quality Manager, Failure Analysis Electrical Engineer
Overview:
In this role you will lead failure analysis on hyperscale AI computing platforms, driving root-cause investigations and corrective actions to enhance reliability. You will collaborate with design, manufacturing, and reliability teams to tackle system- and hardware-level issues across GPUs, CPUs, ASICs, and memory. The position focuses on diagnosing failures from system to component levels and shaping robust reliability validation plans. You will contribute to shaping next-generation AI infrastructure and ensure customer satisfaction through continuous improvement. Compensation / Benefitsmedical, dental, and vision plans Life Insurance Disability (short-term and long-term) Matching 401(k) Contributions Vacation and Paid Sick Time Tuition Reimbursement
Responsibilities:
- Lead failure analysis investigations on hyperscale AI systems (servers, clusters, ASIC platforms, networks, storage, power delivery)
- Diagnose failures from system level down to PCB, component, package, and silicon die levels
- Perform root cause analysis for system boot, thermal, memory, PCIe, power integrity, signal integrity, and AI accelerator failures
- Interpret schematics, board layouts, stack-ups, docs, simulations, and test data to identify failure modes
- Conduct advanced electrical failure analysis (short/open circuits, power rail, leakage, SI/PI, ESD/EOS)
- Apply physical failure analysis methods (cross-sectioning, dye/ pry, decapsulation, SEM, solder joint and package integrity)
- Investigate semiconductor-related failures in GPUs/CPUs/ASICs/FPGAs/HBM and high-speed SerDesDevelop and execute reliability validation plans (thermal cycling, HALT/HASS, burn-in, environmental testing, vibration, shock, accelerated life)
- Collaborate with design, manufacturing, supplier quality, reliability teams, and customers to resolve reliability issues
- Lead technical reviews and communicate findings and corrective actions to stakeholders
- Drive continuous improvement for product quality, reliability, and customer satisfaction
Key requirements:
- Bachelor's degree in Electrical Engineering, Electronics Engineering, Reliability Engineering or related field; Master's preferred
- Minimum 5 years of hands-on reliability/electronics experience 3+ years of managerial experience
- Experience with hyperscale computing systems, AI server platforms, GPU-based systems, ASIC-based products, or data center infrastructure
- Strong knowledge of high-speed digital electronics, SI/PI, PCB technologies and manufacturing, semiconductor packaging and failure mechanisms, thermal management
- Strong communication and collaboration
- Problem-solving and analytical thinking
- Cross-functional teamwork
- Electrical failure analysis
- System, PCB, and silicon-level diagnosticsSI/PI analysis and testing