Sr. Agentic AI Solutions Engineer

Advanced Micro Devices, Inc•Santa Clara, CA

1d•Hybrid

About The Position

ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career. THE ROLE: AMD's Software and Solutions Team is seeking a Senior Agentic AI Solutions Engineer to design, build, and deliver next-generation Agentic AI solutions built on AMD's heterogeneous computing portfolio. Working under the technical direction of AMD's Agentic AI Systems Architecture team, this role drives the hands-on development, integration, and performance optimization of end-to-end AI workflows that leverage AMD CPUs, GPUs, DPUs, networking, and software platforms to deliver secure, scalable, deterministic, and high-performance AI solutions for AMD's most strategic customers. Working across AMD's AI software ecosystem—including AMD + AMD (A+A) and AMD + NVIDIA (A+N) environments—and leveraging ROCm™, AMD Zen Software Studio, AMD Enterprise AI, and AMD's open-source software initiatives, this engineer will translate architectural vision into working customer solutions, reference implementations, and early customer proof-of-concepts (PoCs) across enterprise, cloud, sovereign AI, and edge deployments. Delivered solutions will focus on execution, performance, efficiency, data integrity, and security, including governance, compliance, and AI sovereignty, while providing implementation feedback that helps shape AMD silicon and software roadmaps. This is a deeply hands-on, customer-facing senior individual contributor role focused on solution delivery, technical implementation, and performance engineering. It is not a people management, program management, or alliance management position. THE PERSON: A deep hands-on engineer with strong expertise spanning AI infrastructure, virtualization systems, distributed systems, heterogeneous computing, intelligent data architectures, operating systems, cloud and Neo Cloud environments, networking, security architecture (including secure computing and cryptography), and large-scale AI platform design, complemented by broad experience across modern AI software stacks, enterprise solutions, and software engineering methodologies. This individual has a demonstrated history of delivering complex customer solutions and shipping working systems that span hardware, software, networking, security, and AI frameworks. The ideal candidate understands how frontier foundation models, agentic reasoning systems, orchestration frameworks, intelligent data structures, and heterogeneous compute resources interact to deliver scalable, deterministic, trustworthy, and production-ready AI systems. They thrive in customer-embedded environments where they can turn architectural vision into working code, benchmarks, and customer proof-points leading through technical excellence, deep coding ability, and solution delivery alongside the Fellow-level architect.

Requirements

Strong hands-on experience delivering large-scale AI infrastructure, distributed AI systems, cloud-native AI platforms, or enterprise AI solutions across heterogeneous computing architectures spanning CPUs, GPUs, DPUs, networking, storage, memory subsystems, virtualization, and cloud infrastructure.
Strong understanding of modern AI software ecosystems, including ROCm™, AMD Enterprise AI, AMD Zen Software Studio, frontier foundation models, LLM inference, Retrieval-Augmented Generation (RAG), vector databases, model serving, and AI orchestration frameworks.
Hands-on experience delivering Agentic AI solutions — multi-agent collaboration, orchestration frameworks, autonomous reasoning, planning, workflow optimization, and intelligent task execution.
Deep hands-on expertise in data optimization, intelligent data structures, knowledge representation, vector databases, and retrieval architectures supporting enterprise-scale AI systems.
Strong expertise in AI performance engineering — latency optimization, throughput, token efficiency, inference scalability, workload scheduling, and heterogeneous resource utilization.
Experience delivering methodologies that improve AI reliability through deterministic execution, hallucination mitigation, grounding, explainability, and trusted AI outcomes; working knowledge of confidential computing, trusted execution environments, attestation, data provenance, and enterprise AI security.
Deep hands-on coding ability with strong programming skills in Python, C, C++ and comfort in performance-critical code paths, profiling, and optimization.
Background as a solutions engineer, applications engineer, or technical consultant at a major systems or platform company (e.g., HP, Dell, or comparable) or a top-tier consulting/integration organization is a strong plus.
Excellent written and verbal communication; comfort embedding with customer engineering teams and presenting to senior customer stakeholders.
Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Data Science, or related field preferred; advanced degree desired.

Responsibilities

Deliver on AMD's Agentic AI technical strategy across enterprise, cloud, sovereign AI, edge, and emerging AI deployment environments, translating architectural vision into working customer solutions, reference implementations, and PoCs.
Build and optimize end-to-end reference solutions that maximize heterogeneous execution across AMD CPUs, GPUs, DPUs, networking, memory, storage, and future accelerator technologies — supporting both AMD + AMD (A+A) and AMD + NVIDIA (A+N) deployment models.
Deliver intelligent multi-agent systems and orchestration frameworks that optimize execution across heterogeneous compute resources while balancing performance, latency, throughput, power efficiency, scalability, and cost.
Optimize Agentic AI execution end-to-end — task decomposition, multi-agent collaboration, workflow scheduling, reasoning pipelines, context management, token and inference efficiency, and resource allocation — balancing performance, cost, energy, security, and quality of service across heterogeneous AI infrastructure.
Implement innovative approaches for data optimization and intelligent data structures that improve retrieval efficiency, knowledge representation, inference performance, memory hierarchy utilization, and overall AI system scalability.
Deliver solutions that improve deterministic AI behavior, reduce hallucinations, and increase reliability, explainability, and trustworthiness of Agentic AI systems through grounding techniques, orchestration strategies, policy enforcement, validation frameworks, and intelligent workflow design.
Build trusted, secure AI solutions incorporating data provenance, data attestation, lineage tracking, governance, compliance, and AI sovereignty, leveraging confidential computing, trusted execution environments, hardware roots of trust, attestation, and cryptographic techniques.
Integrate frontier foundation models with retrieval systems, enterprise applications, orchestration frameworks, edge computing, sovereign AI environments, and hybrid cloud deployments.
Partner directly with strategic customers, hyperscalers, OEMs, ISVs, and open-source communities to embed, deliver, and validate AMD Agentic AI solutions in production-oriented environments, accelerating customer adoption and reference outcomes.
Partner with silicon architecture, software engineering, AI framework, and product management teams to provide implementation- and customer-driven feedback that informs future AMD silicon, software, and platform roadmaps.