Responsibilities
THE ROLE:
AMD’s Software and Solutions Team is seeking an Agentic AI Systems Architecture Fellow to define the architectural vision and technical strategy for next-generation Agentic AI systems built on AMD’s heterogeneous computing portfolio. This is a rare opportunity to take deep, hard-won expertise — wherever you built it — and channel it directly into what AMD is building today and where the company is headed next, shaping end-to-end AI workflows that seamlessly leverage AMD CPUs, GPUs, DPUs, networking, and software platforms to deliver
secure, scalable, deterministic, and high-performance AI solutions.
The Fellow will establish AMD’s technical strategy for Agentic AI while developing innovative, real-world use cases that demonstrate the capabilities of AMD platforms through internal implementations and early customer proof-of-concepts (PoCs).
By integrating frontier foundation models, intelligent orchestration frameworks, heterogeneous compute scheduling, and data-centric optimization across enterprise, cloud, sovereign AI, and edge deployments, the Fellow will accelerate adoption of AMD AI technologies while validating next-generation architectural approaches in production-oriented environments — turning personal expertise into AMD’s forward momentum.
Working across AMD’s AI software ecosystem — including AMD + AMD (A+A) and AMD + NVIDIA (A+N) environments — and leveraging technologies such as ROCm™, AMD Zen Software Studio, AMD Enterprise AI
, and AMD’s open-source software initiatives, the Fellow will define reference architectures focused on execution, performance, and efficiency
, while also considering data integrity, security, and governance. These architectures will help AMD customers deploy trusted, scalable, production-ready AI solutions while influencing AMD silicon and software roadmaps to maintain aggressive innovation and market leadership.
As a recognized technical authority, this individual will collaborate with product engineering, silicon architecture, software organizations, customers, hyperscalers, ISVs, open-source communities, and industry partners to shape the future of Agentic AI computing. This is a highly technical individual contributor role focused on architectural innovation, technical strategy, and execution — not a people management, program management, or alliance management position.
THE PERSON:
- A recognized industry expert with deep expertise spanning
- Agentic AI systems architecture, heterogeneous AI infrastructure, and AI performance engineering
- — the three defining pillars of this role. AMD is especially interested in architects with strong
CPU-based platform backgrounds: this role is not GPU-only, and candidates who bring deep CPU systems expertise alongside AI fluency are highly encouraged to apply. You don’t need to be an expert in every domain — heterogeneous computing, distributed systems, intelligent data architectures, operating systems, cloud/Neo Cloud, networking, and security are all valuable, but your strongest platform (CPU or GPU) combined with AI systems depth is what matters most.
The ideal candidate understands how frontier foundation models, agentic reasoning systems, orchestration frameworks, and heterogeneous compute resources interact to deliver scalable, deterministic, and production-ready AI systems, and thrives shaping long-term strategy while staying hands-on in architectural innovation and performance engineering.
KEY RESPONSIBILITIES:
- Define AMD’s architectural vision and long-term technical strategy for Agentic AI, and bring it to life through real-world use cases, reference implementations, and early customer proof-of-concepts.
- Architect end-to-end reference architectures optimizing heterogeneous execution across AMD CPUs, GPUs, DPUs, networking, memory, and storage — with particular attention to CPU-centric platform architectures alongside GPU-based approaches — supporting both
- AMD + AMD (A+A) and
- AMD + NVIDIA (A+N) deployment models.
- Experience with agentic AI benchmarks required including agent orchestration, planning, routing and verification
- Demonstrate advantages of EPYC-based platforms and architecture for agentic workloads vs. other x86 and ARM alternatives
- Partner with Silicon architecture and engineering to define the next-gen features for a holistic A+A advantage
- Architect intelligent multi-agent systems and orchestration frameworks, defining optimization strategies for task decomposition, workflow scheduling, reasoning pipelines, and end-to-end performance across heterogeneous compute resources.
- Develop innovative approaches for data optimization and intelligent data structures
- , and lead integration of frontier foundation models with retrieval systems, enterprise applications, and edge/sovereign AI deployments.
- Drive architectural innovations that improve deterministic AI behavior and reliability, incorporating sound data governance and security practices (including data provenance and trusted execution) as part of a holistic, production-ready architecture.
- Collaborate with silicon architecture, software engineering, and AI framework teams to influence AMD’s future silicon and software roadmaps, and partner with hyperscalers, OEMs, ISVs, and open-source communities to accelerate adoption of AMD AI platforms.
- Represent AMD as a recognized technical authority through customer engagements, industry conferences, and technical publications.
PREFERRED EXPERIENCE:
Top skills we’re looking for:
Agentic AI systems architecture, heterogeneous AI infrastructure, and AI performance engineering — including strong CPU-based platform experience
(GPU-only backgrounds are welcome too, but candidates should not self-select out for lacking GPU-specific depth).
Experience designing large-scale AI infrastructure, distributed AI systems, or enterprise AI architectures across heterogeneous computing platforms — CPUs, GPUs, DPUs, networking, and storage.
Understanding of modern AI software ecosystems, including ROCm™, AMD Enterprise AI, AMD Zen Software Studio, frontier foundation models, LLM inference, sglang, lmcache, RAG, and AI orchestration frameworks.
Experience architecting Agentic AI systems — multi-agent collaboration, orchestration frameworks, autonomous reasoning, and workflow optimization.
Expertise in data optimization, model deployment and supporting enterprise-scale AI systems.
Strong knowledge in AI performance engineering — latency, throughput, token efficiency, and heterogeneous resource utilization.
Familiarity with trusted/secure AI practices (confidential computing, data provenance, governance) is a plus.
Recognized technical leadership through patents, publications/presentations, or open-source contributions.
ACADEMIC CREDENTIALS:
Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Data Science, or a related technical discipline preferred.
ALTERNATE LOCATION:
Santa Clara, CA
This role is not eligible for visa sponsorship.
Qualifications
