Fellow, Customer Quality, Data Center & AI Platform

THE ROLE:

At AMD, we push the boundaries of innovation to solve the world's most important challenges.As a Fellow, Customer Quality, you will driveAI infrastructure qualityfor next-generation data center CPUs and GPUs powering hyperscale and enterprise deployments.

This is a high-visibility role within the Customer Engineering organization, focused on ensuring quality outcomes across customer deployments. You will bridge the gap between internal silicon development and real-world customer environments, translating large-scale deployment signals into actionable insights that improve product and platformquality andreliability.

Working closely with customers,engineeringand the corporate Quality organization, you will drive customer-facing quality metrics, enable closed-loop improvements, and ensure customer-reported issues and system-level behaviors are reflected in product and quality processes.

THE PERSON:

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 atinfluencing acrossengineering, manufacturing, and quality organizations.

You are comfortable operating in complex, fast-paced environments and working directly with hyperscale and enterprise customers. You bringstrong communicationskills, the ability to translate technical insights into actionable improvements, anda track recordof 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 byidentifyingtest 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

PREFERRED EXPERIENCE:

• 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, includinghigh-volume silicon deploymentsin 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)

• Expertisein 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 foundationin system-level quality and reliability analysis across complex silicon or SoC architectures, including large-scale validation or fleet environments

• Track recordof 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

ACADEMIC CREDENTIALS:

Master's, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field preferred

LOCATION:

Austin, TX, Santa Clara, CA or other AMD office locations

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