Design, develop, and deploy multi-agent AI systems (using LLMs, Reinforcement Learning, and Graph Neural Networks) that autonomously analyze RTL topologies, partition large design spaces, and dynamically tune solver parameters. Proven experience building or researching Agentic AI pipelines, multi-agent frameworks (e.g., LangChain, AutoGen, CrewAI), tool-use execution, and prompt-engineering tailored to structured code or hardware descriptions.