Bengaluru Dev Shares Journey From Intern to Building Production RAG Systems

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Ganesh Dhakali, a full-stack Gen AI developer based in Bengaluru, transitioned from intern to full-time engineer by independently shipping an end-to-end AI feature — from database setup to a live streaming response in the browser. He specializes in retrieval-augmented generation (RAG) systems that allow users to query real knowledge bases using natural language, built on a multi-node pipeline with vector search and swappable LLM configurations. A notable challenge he solved involved vector search silently returning zero results after a bulk embedding load, traced to an index built on an empty table — fixed by rebuilding the index post-load. Dhakali emphasizes engineering discipline, including secure APIs, clean Git workflows, and separate QA and production environments. He is now pursuing the Google Cloud Gen AI Academy APAC to deepen his work in agent-based architectures and standardized data integrations like Model Context Protocol.

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