Senior Manager, AI Power & Performance Engineering

Advanced Micro Devices, Inc•Austin, TX

15d•Hybrid

About The Position

The Senior Manager, AI Power & Performance (AI PnP) will lead a team responsible for delivering industry-leading AI performance, power efficiency, benchmarking, characterization, and optimization across AMD's Embedded and Edge AI platforms. This leader will partner closely with architecture, software, silicon, product management, marketing, and customer-facing teams to ensure AMD solutions achieve competitive leadership in AI workloads spanning Robotics, Physical AI, Automotive, Industrial, and Edge Computing. Join a fast-growing organization shaping AMD's vision for Physical AI, Robotics, Automotive, Industrial, and Edge AI solutions. This role offers the opportunity to influence next-generation AI platforms, build world-class engineering teams, and drive technology that powers intelligent systems across a wide range of industries.

Requirements

Proven experience in software engineering, system performance, Edge physical AI, embedded platforms, or related domains.
Proven experience leading engineering teams and delivering complex technical programs.
Proven experience in Power and Power PnP activities Pre-Silicon and Post-Silicon & Correlation
Strong understanding of AI/ML frameworks, inference runtimes, and performance optimization techniques.
Experience with heterogeneous computing architectures involving CPUs, GPUs, NPUs, and accelerators.
Excellent communication, organizational, and leadership skills.
Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field.

Nice To Haves

Experience with AMD AI technologies including ROCm, Ryzen AI, ONNX Runtime, MIGraphX, or other AI software stacks.
Experience in Robotics, Physical AI, Automotive, Industrial, or Edge AI markets.
Familiarity with generative AI, multimodal AI, computer vision, and robotics workloads.
Knowledge of AI benchmarking, profiling tools, performance analysis, and power optimization techniques.
Experience working with geographically distributed engineering organizations.

Responsibilities

Define and execute AI power and performance strategy across AMD CPU, GPU, NPU, and heterogeneous computing platforms.
Establish benchmarking methodologies, performance KPIs, competitive analysis frameworks, and workload characterization processes.
Drive performance optimization across AI models, runtimes, kernels, frameworks, and system software stacks.
Identify bottlenecks and influence hardware, firmware, runtime, and software roadmap decisions through data-driven analysis.
Lead performance readiness for AI solutions across Robotics, Physical AI, Automotive, Industrial, and Edge AI markets.
Develop customer-ready performance collateral, benchmarking reports, tuning recommendations, and competitive positioning data.
Partner with software engineering teams to validate AI models, inference pipelines, SDKs, frameworks, and application workloads.
Ensure performance scalability, efficiency, reliability, and production readiness across deployed solutions.
Build, lead, mentor, and grow a high-performing global engineering organization consisting of AI performance, benchmarking, and automation engineers.
Establish clear goals, execution plans, staffing strategies, and career development programs.
Foster a culture of innovation, accountability, technical excellence, and customer obsession.
Support strategic customer engagements, design-win efforts, technical escalations, and performance-related discussions.
Collaborate with Product Management, Architecture, Software Engineering, Marketing, and Field Engineering teams to define and execute winning AI platform strategies.
Represent AMD performance leadership in executive reviews, customer meetings, and industry engagements.
Drive development of scalable benchmarking, automation, telemetry, profiling, and analytics infrastructure.
Establish continuous performance validation frameworks and dashboards for workload tracking and regression analysis.
Improve engineering efficiency through CI/CD integration and automated performance qualification systems.