The Lead System Validation Engineer - AI Rack Validation at AMD will be responsible for system and silicon validation of AMD EPYC Server and AMD Instinct products. This role involves leading a post-silicon validation group, focusing on system-level failures and developing validation strategies for optimal debug throughput. The engineer will collaborate with various engineering teams to enhance product quality and drive improvements in validation methodologies. This position requires strong technical leadership and a collaborative approach to tackle complex challenges in a global environment.

• Extensive experience in validation roles involving debugging OS, firmware, silicon, and hardware issues.
• Strong knowledge of X86 architecture, SoC design, memory, RAS, and power management.
• Good understanding and experience in platform/system level debug, operating systems, device drivers, and system BIOS interactions.
• Excellent communication and coordination skills.
• Strong analytical and problem-solving skills with attention to detail.
• Bachelor's or Master's degree in electrical or computer engineering preferred.

• Lead system-level, rack-level, and cluster-scale validation strategy for AI and machine learning server platforms.
• Define and drive comprehensive validation plans covering customer deployment scenarios across scale-up and scale-out environments.
• Develop validation methodologies and test strategies spanning CPU, GPU, memory, BIOS, BMC, networking, storage, platform firmware, operating systems, and infrastructure components.
• Collaborate with architecture, hardware, firmware, software, and platform engineering teams to define validation requirements and improve overall product quality.
• Lead investigation and root cause analysis of complex hardware, firmware, software, networking, and system integration issues.
• Drive technical decision-making within the validation organization and influence cross-functional teams to resolve critical product risks.
• Define and enhance scalable validation frameworks, automation infrastructure, and data-driven validation methodologies.
• Analyze large-scale validation data to identify systemic failures and product readiness concerns.
• Establish validation readiness criteria, quality metrics, and coverage strategies to improve execution efficiency.
• Mentor and provide technical leadership to engineers to improve validation methodologies and debugging effectiveness.
• Drive execution across multiple validation programs while managing priorities, dependencies, and technical risks.
• Communicate validation status, readiness assessments, and key risks to senior technical leadership.

• AMD provides a competitive 'Total Rewards' package that focuses on financial growth, health, and work-life balance.