AMD is seeking a Lead System Validation Engineer - AI Rack Validation to join our post-silicon validation team. You will lead system-level, rack-level, and cluster-scale validation for AI and machine learning server platforms, focusing on AMD EPYC Server and Instinct products. Define and drive validation plans across scale-up and scale-out environments, and develop methodologies and 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, identify coverage gaps, and improve overall product quality. Lead investigation and root cause analysis of complex hardware, firmware, software, networking, and system integration issues; drive technical decisions within the validation organization and coordinate with cross-functional teams to resolve risks and quality concerns. Define scalable validation frameworks, automation infrastructure, telemetry-driven workflows, and data-driven validation methodologies. Analyze large-scale validation data to identify systemic failures, reliability risks, performance bottlenecks, and readiness concerns. Establish readiness criteria, quality metrics, and coverage strategies to improve execution efficiency and early risk identification. Mentor engineers and provide technical leadership to improve validation methodologies, automation capabilities, debugging effectiveness, and system-level engineering practices. Manage multiple validation programs

AMD is seeking a Lead System Validation Engineer - AI Rack Validation to join our post-silicon validation team. You will lead system-level, rack-level, and cluster-scale validation for AI and machine learning server platforms, focusing on AMD EPYC Server and Instinct products. Define and drive validation plans across scale-up and scale-out environments, and develop methodologies and 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, identify coverage gaps, and improve overall product quality. Lead investigation and root cause analysis of complex hardware, firmware, software, networking, and system integration issues; drive technical decisions within the validation organization and coordinate with cross-functional teams to resolve risks and quality concerns. Define scalable validation frameworks, automation infrastructure, telemetry-driven workflows, and data-driven validation methodologies. Analyze large-scale validation data to identify systemic failures, reliability risks, performance bottlenecks, and readiness concerns. Establish readiness criteria, quality metrics, and coverage strategies to improve execution efficiency and early risk identification. Mentor engineers and provide technical leadership to improve validation methodologies, automation capabilities, debugging effectiveness, and system-level engineering practices. Manage multiple validation programs