Sr. Staff Software Engineer - AI Agentic Infrastructure & Systems
About The Position
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.
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 Haves
- Hardware Verification: Hands-on experience with Board Bring-up and proficiency with low-level diagnostic tools such as JTAG, xbutil, and dmesg.
- Experience with AMD Vitis or AIE programming.
- Compiler Background: Proficiency with semantic analysis
- Familiarity with computational complexity theory and its application to software efficiency
Responsibilities
- 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 using LangChain (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 using LangGraph to 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: Utilize LangSmith for deep trace analysis, debugging complex agent trajectories, and optimizing prompt/chain latency and cost.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
