Product Development Engineer - AI Systems

Advanced Micro Devices, Inc • Austin, TX

14h • Hybrid

About The Position

AMD is building the next generation of AI-powered analytics platforms to transform how semiconductor engineers and analysts understand yield, test, and quality data. In this role, you will help design and build multi-agent, LLM-driven systems that assist engineers in investigating complex questions—such as yield loss, defect trends, customer returns, and emerging failure mechanisms. You will work in a highly collaborative environment alongside AI architects, software engineers, product leaders, and semiconductor domain experts. Your focus will be on developing intelligent systems where AI agents can reason over structured data, propose hypotheses, and guide users toward root causes—while maintaining transparency, traceability, and strong human-in-the-loop controls. This role offers the opportunity to work on real, high-impact problems at the intersection of AI, data platforms, and semiconductor manufacturing. You are a strong systems-oriented software engineer who enjoys working on complex, data-driven problems. You are curious, analytical, and comfortable operating in areas where requirements may initially be ambiguous. You value collaboration, can communicate clearly across technical and non-technical audiences, and are motivated by building practical AI solutions that engineers can trust and use in their daily workflows.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Nice To Haves

• Strong software engineering fundamentals, including system design, debugging, and API development.
• Proficiency in Python and experience building backend or data-centric systems.
• Hands-on experience working with large language models (commercial or open-source).
• Comfort working with structured data, such as SQL databases, dataframes, and analytics outputs.
• Experience with agentic AI frameworks (e.g., LangChain, LangGraph, LlamaIndex).
• Familiarity with vector databases and hybrid retrieval approaches.
• Experience building analytics-heavy or data-intensive products.
• Exposure to LLM evaluation and testing, including quality and regression assessment.
• Understanding of distributed systems, asynchronous workflows, or microservices.
• Experience collaborating with domain experts to translate problem knowledge into software solutions.

Responsibilities

• Design and develop multi-agent analytics workflows, enabling specialized AI agents to collaborate on data retrieval, hypothesis generation, root-cause analysis, and insight summarization.
• Implement agent orchestration logic, including task decomposition, planning, routing, and inter-agent communication.
• Integrate large language models with structured data sources, analytics engines, and internal APIs using tool and function-calling techniques.
• Build and manage state, memory, and context handling to support multi-step analytical reasoning.
• Develop and maintain retrieval-augmented generation (RAG) pipelines over enterprise and domain-specific datasets.
• Apply guardrails, evaluation strategies, and observability to ensure AI systems are reliable, explainable, and production-ready.
• Partner closely with domain experts to capture and encode tribal knowledge as reusable AI capabilities.
• Contribute to shared architectural patterns and agent frameworks used across teams.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees