Agentic AI Systems Architect (Heterogeneous CPU/GPU)

AMD

Austin (TX)

On-site

USD 250,000 - 350,000

Full time

9 days ago

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Job summary

AMD is seeking an Agentic AI Systems Architecture Fellow to define the architectural vision for next-generation Agentic AI. You will shape end-to-end AI workflows, integrating frontier foundation models with intelligent orchestration across AMD CPUs, GPUs, DPUs, networking, and software.

Role requires deep CPU-based platform expertise alongside AI fluency, collaborating across product engineering, silicon teams, and customers to drive production-ready, secure AI solutions and influence AMD

Qualifications

  • Experience designing large-scale AI infrastructure across heterogeneous computing platforms.
  • Experience architecting Agentic AI systems—multi-agent coordination and orchestration.
  • Strong collaboration with product engineering, silicon architecture, and AI framework teams.

Responsibilities

  • Define AMD’s architectural vision and long-term strategy for Agentic AI with real-world use cases and PoCs.
  • Architect end-to-end reference architectures optimizing heterogeneous execution across CPUs, GPUs, DPUs, networking, memory, and storage.
  • Demonstrate advantages of EPYC-based platforms for agentic workloads and contribute to next-gen features.
  • Partner with silicon architecture and engineering to define future features and roadmaps.
  • Collaborate with external partners to accelerate adoption of AMD AI platforms.

Skills

Agentic AI systems architecture
Heterogeneous AI infrastructure
AI performance engineering
CPU-based platform expertise
Cross-functional collaboration

Education

Master’s degree in Computer Science or related field

Tools

ROCm
AMD Zen Software Studio
AMD Enterprise AI

Job description

AMD is seeking an Agentic AI Systems Architecture Fellow to define the architectural vision for next-generation Agentic AI. You will shape end-to-end AI workflows, integrating frontier foundation models with intelligent orchestration across AMD CPUs, GPUs, DPUs, networking, and software.

Role requires deep CPU-based platform expertise alongside AI fluency, collaborating across product engineering, silicon teams, and customers to drive production-ready, secure AI solutions and influence AMD

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