Google

During my internship at Google in the AI Engineering team, I worked on building RAG-based AI Agents to revolutionize how researchers discover and apply for grants. My work directly impacted over 10,000 researchers by helping them match with relevant grants, generate applications, and find potential co-authors.

I engineered sophisticated hybrid search and re-ranking algorithms that leveraged grant metadata, user queries, and researcher profiles to deliver highly personalized recommendations across a database of over 80,000 grants. This system significantly improved the grant discovery process for academic researchers.

My role involved building scalable cloud infrastructure using Terraform and BigQuery, developing Python-based agentic tools for data retrieval and processing, and architecting custom MLOps evaluation pipelines. The solutions I built handled over 20,000 daily requests while reducing agent-workflow latency by 40%.