AI-focused Python Developer

I am an AI-focused Python developer specializing in production-grade Retrieval-Augmented Generation (RAG) applications, agentic workflows, and deterministic API automations.

I build source-grounded AI solutions using LangChain, LangGraph, vector databases, and large language models. My work includes document ingestion, chunking, embeddings, structured JSON schema extraction, semantic retrieval, and context-grounded responses.

I have hands-on experience designing agentic workflows with stateful routing, error handling, fallback mechanisms, conversation memory, and tool/function calling. I focus on reducing hallucinations and improving extraction reliability in complex document-processing use cases.

I develop hybrid search systems that combine dense vector embeddings, BM25-style retrieval, metadata filtering, reranking, and vector databases such as Qdrant, ChromaDB, Supabase pgvector, and Pinecone.

I also create automation and application interfaces using n8n, Flowise, Streamlit, FastAPI, webhooks, and REST APIs. I am comfortable working with cloud and data tools including AWS, PostgreSQL, MySQL, CUDA, Power BI, and Excel.

I am motivated by rapidly prototyping scalable AI workflows that solve operational and data-processing bottlenecks through low-latency, reliable, and practical LLM-based systems.