4 days ago
Santa Clara, CA, USASenior
Responsibilities
- Deliver Agentic AI technical strategy through customer solutions, reference implementations, and proof-of-concepts.
- Build and optimize end-to-end AI solutions across CPUs, GPUs, DPUs, networking, memory, storage, and accelerator technologies.
- Develop multi-agent systems and orchestration frameworks that optimize performance, latency, throughput, efficiency, scalability, and cost.
- Optimize task decomposition, reasoning pipelines, context management, inference efficiency, workflow scheduling, and resource allocation.
- Develop data optimization, intelligent data structure, knowledge representation, and retrieval solutions for scalable AI systems.
- Improve AI reliability, determinism, explainability, trustworthiness, and hallucination mitigation through grounding, validation, policy enforcement, and workflow design.
- Build secure AI solutions using data provenance, governance, compliance, confidential computing, trusted execution environments, attestation, and cryptography.
- Integrate foundation models with retrieval systems, enterprise applications, orchestration frameworks, edge environments, and hybrid clouds.
- Embed with strategic customers and partners to deliver and validate AMD Agentic AI solutions in production-oriented environments.
- Provide customer and implementation feedback to AMD silicon, software, AI framework, and product management teams.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Data Science, or a related field is preferred; an advanced degree is desired.
- Strong hands-on experience delivering large-scale AI infrastructure, distributed AI systems, cloud-native AI platforms, or enterprise AI solutions across heterogeneous computing architectures.
- Experience with modern AI ecosystems, ROCm, AMD Enterprise AI, AMD Zen Software Studio, foundation models, LLM inference, Retrieval-Augmented Generation, vector databases, model serving, and AI orchestration frameworks.
- Hands-on experience delivering Agentic AI solutions involving multi-agent collaboration, orchestration, autonomous reasoning, planning, workflow optimization, and intelligent task execution.
- Deep expertise in data optimization, intelligent data structures, knowledge representation, vector databases, and retrieval architectures.
- Strong AI performance engineering experience involving latency, throughput, token efficiency, inference scalability, workload scheduling, and heterogeneous resource utilization.
- Experience improving 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.
- Strong programming ability in Python, C, and C++, including performance-critical code, profiling, and optimization.
- Background as a solutions engineer, applications engineer, or technical consultant at a major systems or platform company or top-tier consulting/integration organization is a strong plus.
- Excellent written and verbal communication skills and comfort embedding with customer engineering teams and presenting to senior customer stakeholders.
Benefits
- Hybrid work arrangement; an alternate location is Austin, Texas.
- AMD benefits are offered as described in the company’s benefits overview.
About AMD
AMD designs and sells CPUs, GPUs, and adaptive/embedded computing products for PCs, data centers, gaming, and edge devices. Its portfolio includes Ryzen and EPYC processors, Radeon and Instinct graphics, and adaptive SoCs from its Xilinx acquisition, sold to OEMs, cloud providers, and device makers. Founded in 1969 and headquartered in Santa Clara, it is a public company on NASDAQ and supplies semi-custom chips for major game consoles.