Job Summary
As a Customer Quality Engineer,
The ideal candidate is a strategic and technically deep leader with a strong customer-first mindset and a passion for improving quality outcomes at scale. You are highly collaborative and effective at influencing across engineering, manufacturing, and quality organizations.
You are comfortable operating in complex, fast-paced environments and working directly with hyperscale and enterprise customers. You bring strong communication skills, the ability to translate technical insights into actionable improvements, and a track record of driving alignment across cross-functional teams
Key Responsibilities
- Drive customer quality outcomes across AI and data center infrastructure deployments, ensuring high reliability in production environments
- Translate fleet-scale signals and customer issues into actionable improvements across product, validation, and manufacturing
- Monitor and improve customer-facing quality metrics across hyperscale and enterprise deployments
- Apply advanced reliability methodologies, including physics-based modeling and statistical analysis, to improve quality outcomes
- Enable predictive approaches that support high-confidence deployments at scale
- Partner with architecture, design, manufacturing, OSAT, and the corporate Quality organization to align on quality priorities
- Influence cross-functional decisions to improve product and platform quality outcomes
- Support product launch readiness by identifying test gaps and driving improvements in validation and qualification
- Provide feedback from customer deployments to improve manufacturing screening, defect detection, and DPM performance
- Strengthen feedback loops between customer environments and internal engineering teams
Skill Requirements
- Several years of experience in semiconductor product quality, customer quality, or silicon manufacturing quality
- Background in semiconductor product quality, customer quality, or silicon manufacturing quality, including high-volume silicon deployments in hyperscale or enterprise environments
- Deep understanding of data center CPUs, GPUs, or AI accelerator platforms, including server system architecture (compute, memory, I/O, and RAS)
- Expertise in product reliability methodologies, manufacturing quality systems, and product qualification processes
- Demonstrated ability to translate customer and system-level failures into improvements in product design, test coverage, and manufacturing screening
- Proven capability in defining test patterns and system-level validation methodologies to detect time-zero and reliability defect modes
- Strong foundation in system-level quality and reliability analysis across complex silicon or SoC architectures, including large-scale validation or fleet environments
- Track record of influencing cross-functional teams and driving quality improvements across engineering, manufacturing, and quality organizations
- Experience collaborating with foundry and OSAT partners to achieve defect-per-million (DPM) targets and improve manufacturing outcomes
- Familiarity with advanced silicon technologies, heterogeneous compute, or high-performance computing architectures