Principal Platform Power and Performance Engineer

Provide technical leadership and mentorship for a team of highly skilled engineers while leading cross-functional initiatives that solve complex platform power, performance, and efficiency challenges. Partner with business, architecture, silicon, firmware, hardware, validation, operating systems, manufacturing, and customer engineering teams to define requirements and deliver optimized platform solutions. Drive silicon and platform power-performance architecture, including workload characterization, power management features, frequency/voltage optimization, memory subsystem efficiency, accelerator utilization, and system-level performance tuning. Analyze and optimize interactions between silicon, power delivery, thermal solutions, firmware, operating systems, and datacenter infrastructure to maximize performance, efficiency, reliability, and operational scalability. Lead power-performance characterization, profiling, and benchmarking across Azure datacenter deployments using customer workloads, AI training and inference applications, and synthetic benchmarks to guide data-driven design decisions. Influence future silicon and platform roadmaps through deep analysis of workload behavior, performance bottlenecks, power efficiency opportunities, and emerging AI infrastructure requirements. Communicate technical strategies, tradeoffs, and recommendations to engineering leadership and executive stakeholders, driving alignment across organizations and accelerating delivery of next-generation AI infrastructure. Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 7+ years technical engineering experience OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 8+ years technical engineering experience OR equivalent experience 8+ years of relevant experience in compute and/or AI systems/platforms design and development. 8+ years of experience with SoC, CPU, GPU, or AI accelerator architectures, including power management, performance analysis, memory subsystems, interconnects, power delivery, and thermal solutions. 8+ years of experience collaborating across hardware, firmware, operating systems, silicon architecture, and validation engineering teams to deliver platform solutions. These requirements include but are not limited to the following specialized security screenings: Experience with hyperscale cloud infrastructure, large-scale AI compute platforms, and datacenter operations. Experience with custom silicon, AI accelerators, and silicon bring-up from pre-silicon validation through production deployment. Knowledge of server architecture, power delivery systems, and liquid cooling technologies. Experience with workload characterization, profiling, benchmarking, and performance analysis for AI/ML workloads in large-scale datacenter environments. Experience optimizing performance, efficiency, and performance-per-watt across hardware and software systems. Experience leading cross-functional technical initiatives spanning multiple engineering disciplines.