Neha D.

Most AI engineers can call an API. Few understand the data infrastructure that makes it production-ready. I bring both. With 3+ years building end-to-end AI systems for enterprise clients, I specialize in Retrieval Augmented Generation (RAG) pipelines, multi-agent workflows, LLM application development, OCR & document automation, and scalable data pipelines built specifically for AI workloads. Every deliverable I ship is containerized, tested, and built for real-world scale — not a hackathon prototype. If your AI needs to hold up under production load, you need more than a prompt engineer. What I build: ✦ RAG pipelines & vector database integration (FAISS, ChromaDB) ✦ Multi-agent systems (LangChain, CrewAI) ✦ LLM chatbot development (GPT-4, Claude API, OpenAI API) ✦ Document automation & OCR ✦ AI-optimized data pipelines (PySpark, Kafka, Databricks, Snowflake) ✦ Production APIs (FastAPI, Docker, PostgreSQL) If you're building AI that needs to actually work at scale — let's talk.