AI Systems Validation Engineer

Advanced Micro Devices, Inc•Secaucus, NJ

1d•Onsite

About The Position

This role focuses on leading system-level, rack-level, and cluster-scale validation for next-generation AI and machine learning platforms. You will define validation strategies, drive technical direction, and lead complex validation initiatives across hardware, firmware, software, and infrastructure domains. You will work closely with architecture, platform engineering, silicon design, firmware, software, and deployment teams to ensure product quality, reliability, and deployment readiness at scale. The role requires deep technical expertise, strong analytical skills, and the ability to influence technical decisions across multiple engineering organizations. You will be responsible for establishing validation methodologies, driving execution across large-scale validation environments, and identifying quality risks that impact product readiness and customer deployments.

Requirements

Technical leader with extensive experience in system-level validation and large-scale server platforms.
Thrive on solving complex technical problems, driving cross-functional initiatives, and defining scalable validation approaches for emerging technologies.
Comfortable operating with minimal supervision while providing technical leadership across engineering teams.
Strong debugging skills, sound technical judgment, and a deep understanding of hardware-software interactions.
Proactively identify technical risks, drive resolution of complex platform issues, and influence engineering decisions that improve product quality, validation effectiveness, and deployment readiness.
Passionate about mentoring engineers and elevating engineering excellence across the organization.
Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.

Nice To Haves

8+ years of experience in system-level validation, platform validation, post-silicon validation, large-scale infrastructure validation, or related engineering disciplines.
Proven experience validating large-scale server, AI, cloud, HPC, or data center platforms.
Demonstrated ability to lead investigation and resolution of complex hardware, firmware, software, networking, and infrastructure issues.
Experience validating scale-up and scale-out architectures, including rack-scale and cluster-scale deployments.
Deep understanding of computer architecture, server platform design, operating systems, networking, storage, and hardware/software interactions.
Experience developing automated validation frameworks, orchestration systems, and large-scale test infrastructure.
Strong proficiency in Python and Linux environments, with working knowledge of Bash and/or PowerShell.
Experience leveraging telemetry, analytics, and data-driven methodologies to improve validation coverage, efficiency, and root cause analysis.
Familiarity with AI, machine learning, GPU computing, or accelerated computing environments deployed in data center infrastructures.
Demonstrated ability to lead cross-functional technical initiatives and influence engineering decisions across organizational boundaries.
Experience mentoring engineers and driving technical excellence within validation and product engineering organizations.
Experience supporting product readiness, customer deployment validation, and release qualification activities.
Strong communication skills with the ability to convey technical risks, recommendations, and status to executive and technical leadership.

Responsibilities

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, 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 decision-making within the validation organization and influence cross-functional teams to resolve critical product risks and quality concerns.
Define and enhance 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 product readiness concerns.
Establish validation readiness criteria, quality metrics, and coverage strategies that improve execution efficiency and provide early risk identification.
Mentor and provide technical leadership to engineers, helping improve validation methodologies, automation capabilities, debugging effectiveness, and system-level engineering practices.
Drive execution across multiple validation programs while managing priorities, dependencies, schedules, and technical risks.
Communicate validation status, readiness assessments, quality metrics, technical recommendations, and key risks to senior technical leadership and management.
Support customer-focused validation efforts by ensuring test environments accurately represent real-world deployment conditions and hyperscale operating environments.
Drive continuous improvements in validation processes, tools, and automation to improve organizational efficiency, test coverage, and product quality.