Solution Architect - Physical AI

AMD - Advanced Micro Devices

Belfast, United Kingdom

THE ROLE

AMD is seeking a Solution Architect – Physical AI to help plan, architect, design, and execute our Physical AI product roadmap. In this role, you will work across silicon, software, and system architecture to enable next‑generation Physical AI platforms and customer solutions

THE PERSON

The ideal candidate is an experienced Physical AI Solution Architect who thrives in a fast‑paced, cross‑functional environment and is motivated by solving complex system‑level challenges at the intersection of AI, hardware, and real‑world systems.

You bring strong architectural judgment, a customer‑focused mindset, and experience designing robust, deterministic systems where reliability, predictability, and safety are first‑order design constraints.

KEY RESPONSIBILITIES

Partner with silicon planning and platform architecture teams to help define silicon features and software stacks for next‑generation Physical AI systems;
Collaborate with market segment architects and business leaders to create customer‑focused Physical AI solutions addressing complex requirements across Aerospace, Automotive, Medical, Robotics, Industrial, and Vision markets;
Architect heterogeneous AI systems (CPU + GPU + NPU, FPGA);
Work closely with software engineering and product planning teams to define all aspects of the Physical AI software stack, including:
- ROCm and Ryzen™ AI software support for iGPUs and NPUs;
- AMD’s Virtualized Automotive Stack;
- Robot Operating System (ROS);
- Multimedia analytics pipelines, AI models, and Vision‑Language Models (VLMs) and Large Language Models (LLMs).
Evaluate and communicate system‑level tradeoffs and architectural decisions required to deploy AI in real‑time, deterministic, and safety‑constrained environments.

PREFERRED EXPERIENCE

Experienced Electrical, Computer, or Systems Engineer with deep experience architecting AI‑enabled systems for robotics, automation, autonomous machines, or other safety‑critical/mission‑critical systems;
Hands‑on experience with AI inference hardware (GPU and NPU) and associated software stacks;
Experience with robotics application frameworks and system integration;
Demonstrated ability to break down large, complex problems into manageable deliverables and to manage and prioritize requirements across multiple stakeholders.