AI/Machine Learning Engineer — LangChain-based RAG systems for document QA and medical record intelligence (Aug 2025 – Present)
Built LangChain-based RAG systems that ingest and index medical and business documents for knowledge retrieval and internal reporting. Converted uploaded medical PDFs/images and documents into structured, queryable insights using embeddings and vector databases. Supported applied AI/ML research tied to retrieval methods and production-grade AI architecture for downstream QA and retrieval performance. • Designed and deployed document querying workflows using embeddings and vector databases. • Implemented summarization and “document intelligence” tooling for structured outputs. • Integrated FastAPI backends with Supabase/PostgreSQL and production infrastructure. • Led and trained team members (junior engineers, interns, data analysts, data scientists) on practical AI/ML workflows.