5 days ago
Responsibilities
- Design and maintain multi-agent orchestration with context management, guardrails, progress tracking, crash recovery, audit trails, and communication protocols.
- Build and improve RAG pipelines covering document ingestion, chunking, embeddings, hybrid search, reranking, and knowledge graph indexing.
- Develop web applications, developer experiences, observability dashboards, and operational tooling for AI agents and validation workflows.
- Design distributed services, APIs, event-driven architectures, microservices, and scalable low-latency AI services.
- Build LLM-powered tooling for test-plan generation, test-case auditing, failure triage, knowledge curation, and report generation.
- Deploy agentic AI solutions and translate hardware-validation requirements into software capabilities.
- Address security, privacy, credential handling, observability, automated testing, monitoring, CI/CD, and infrastructure provisioning.
- Own features end to end from estimation and architecture through deployment, measurement, onboarding, and operational improvement.
Requirements
- Production software development experience with a strong portfolio of production systems.
- Hands-on experience shipping LLM-powered systems and building production RAG pipelines, including embeddings, vector databases, chunking, retrieval evaluation, hybrid search, and reranking.
- Experience with LLM tool use, multi-agent orchestration, prompt engineering, context management, and hallucination mitigation.
- Strong proficiency in one or more of Python, TypeScript/Node.js, Go, Java, C#, or Rust; Python is preferred.
- Experience with async programming, API design, distributed systems, reliability, crash recovery, audit trails, state management, and observability.
- Experience with AWS, Azure, or GCP, including infrastructure provisioning, managed services, networking, and production deployment at scale.
- Experience building modern web applications with React, Next.js, Angular, Vue, or similar frameworks.
- Active use of AI coding assistants and LLM-powered developer tools.
- BS or MS degree in Computer Science, Electrical Engineering, or a related field.
- Preferred experience with MCP, Claude Code, LangGraph, CrewAI, AutoGen, Neo4j, LightRAG, graph-augmented RAG, CI/CD, automated test infrastructure, Slack API, GitHub API, Atlassian REST APIs, data pipelines, ETL, data warehousing, or analytics platforms.
- Semiconductor, datacenter, networking, hardware-validation, or firmware-development experience is preferred.
Benefits
- AMD benefits are referenced through its benefits-at-a-glance materials.
- The role is located in Santa Clara, Austin, Seattle, or Secaucus.
- This position is not eligible for visa transfer or sponsorship.
Tech Stack
Categories
About AMD
We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_