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AMD Logo AMD · IT - Software Development

Principal GPU/NPU AI System Architect

United States, Austin 200000.00 - 300000.00 USD / Year · Job Posted March 04, 2026
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Job Description

The AI Architect will define and drive end‑to‑end AI system architecture for embedded and edge platforms, with deep expertise in GPU/NPU micro‑architecture, AI software stacks, and model behavior. This role bridges silicon capabilities, system software, and AI models, enabling performant, power‑efficient, and safe AI deployments across robotics, automotive, and industrial markets.

Job Responsibility

  • Develop deep architectural understanding of GPU, NPU, and heterogeneous SoC designs
  • Guide HW–SW co‑optimization strategies for AI workloads
  • Influence silicon and platform roadmaps using model‑driven architectural insights
  • Collaborate across silicon, system engineering, software, thermal/mechanical, security, and product teams
  • Technically lead internal AI engineers and work closely with partners, ISVs, and customers
  • Act as a technical authority and mentor
  • Architect AI solutions with strong understanding of model internals
  • Evaluate and map model characteristics onto GPU/NPU execution
  • Drive model optimization strategies
  • Define and optimize AI software stacks
  • Lead solutioning for edge and embedded deployment
  • Ensure scalability from prototype → production → long‑term maintenance
  • Translate domain use‑cases into architectural requirements and reusable platform capabilities

Requirements

  • Deep expertise in GPU and/or NPU architecture and execution models
  • Strong hands-on experience with AI models and inference pipelines
  • Proven background in embedded / edge AI systems
  • Strong understanding of hardware-aware model optimization techniques
  • Experience in robotics, automotive, or industrial AI domains
  • Ability to translate customer problems into scalable architectural solutions
  • Motivating leader with good interpersonal skills
  • cross-functional & external leadership
  • Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent
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