Sr. Staff Software Engineer - AI Agentic Infrastructure & Systems
Role details
Job location
Tech stack
Job description
At AMD, we are redefining the paradigm of low-level system software development. We are seeking a Senior Staff Software Engineer to develop the deep integration of high-autonomy agents (e.g., Claude Code, Cursor) into our system software development workflow.
In this role, you will architect an automated, closed-loop system - from requirement description to engineering task verification. By leveraging Verification-Driven Engineering and Feasibility Analysis to determine solvability within existing frameworks, while enabling the Agent to autonomously acquire and synthesize new skills through iterative self-learning, you will transform complex low-level engineering challenges into predictable, controlled agentic tasks, while architecting autonomous agents capable of independent problem-solving and self-evolving technical skills., 1. Architect Verification-Driven Agentic Workflows, * Multi-Agent Collaboration:Implement strategies involving specialized roles (e.g., infra-Architect, Debug-Coder, QA-Validator) to ensure high-quality engineering task output and minimize hallucinations.
- Domain-Knowledge Centric RAG:Build high-precision retrieval systems usingLangChain (LCEL)to index massive repositories, PDFs, and Confluence pages, utilizing advanced strategies like Parent Document Retrieval and Semantic Chunking.
- Complex State Machines:Design and implement cyclic, multi-step reasoning architectures usingLangGraphto manage long-running coding tasks and "reflection" loops.
- Autonomous Execution & Self-Correction
- Zero-Touch Provisioning:Develop systems where agents autonomously set up sandboxed runtimes, resolve dependencies, and configure infrastructure.
- Autonomous Test Synthesis:Architect engines that generate edge-case reproduction scripts and validate fixes within isolated CI/CD pipelines.
- Self-Healing Remediation:Engineer loops that enable agents to parse execution logs, identify root causes, and iteratively apply patches until tests pass.
- Benchmarking & Optimization
- Performance Evaluation:Lead the evaluation of agentic performance using industry-standard benchmarks (e.g.,SWE-bench), aiming for top-tier recovery rates.
- Trace Analysis:UtilizeLangSmithfor deep trace analysis, debugging complex agent trajectories, and optimizing prompt/chain latency and cost., AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
Requirements
- AI Agent Architecture:Proficient in architecting autonomous AI agents using LangGraph, AutoGen, and LangChain. Proven experience in building self-correcting engineering workflows and validating performance via benchmarks like SWE-bench.
- System Programming Excellence:Deep experience in C/C++, with expert knowledge of Linux, memory management, and interrupt handling. Familiar with modern software development process, including complex CI/CD pipelines.
- MCP and Skills Development: Experience in custom MCP Servers and Skills.
- AI Developer Insight:Advanced user of AI tools (Cursor, Claude Code) or developer of LLM-based agentic plugins. Deep understanding of Prompt Engineering and debugging strategies for non-deterministic systems.
- Engineering Philosophy:Strong belief in "Verification as the Boundary." Ability to decompose complex NP-level engineering problems into automatically verifiable P-level tasks.
NICE TO HAVE:
- Hardware Verification:Hands-on experience with Board Bring-up and proficiency with low-level diagnostic tools such as JTAG,xbutil, anddmesg.
- Experience with AMD Vitis or AIE programming.
- Compiler Background: Proficiency with semantic analysis
- Familiarity with computational complexity theory and its application to software efficiency
ACADEMIC CREDENTIALS:
- Master's or PhD in Electrical Engineering, Computer Science, or related field.
