I’m an electrical engineer who has been pivoting into software and AI-focused work by building practical solutions for test automation and engineering workflows. For the past several years at AMD, I worked in FPGA design solutions verification and formed a small team to explore how LLMs can improve verification—especially through retrieval-augmented generation (RAG) and agentic coding patterns.
I enjoy turning domain-specific rules and datasets into reliable software artifacts, using Python and modern LLM tooling to generate, review, and validate outputs. In parallel, I’ve continued re-skilling through hands-on RAG projects with LangChain and OpenAI APIs, and I’m excited to return to roles where I can combine strong engineering foundations with applied AI development to deliver measurable impact.
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