Anil Narayan

Background

About Anil Narayan

Hands-on Engineering leader at the intersection of data, cloud, and AI/ML. From raw data → pipelines → agentic orchestration, turn complexity into scalable, intelligent platforms that ship business value. 20+ years progressing from high-performance Unix/Oracle/ETL automation to cloud modernization and GenAI systems that power real-time personalization and decisioning. Blend hands-on architecture with product thinking: build cost-efficient AWS data estates; design resilient pipelines moving millions of records daily; and deliver AI-native capabilities—LLM-powered search, multi-agent planners/executors, and closed-loop orchestration that moves from insight to action using Vector DBs. Fluent across today’s AI/ML stack: TensorFlow, PyTorch, scikit-learn, Keras, Hugging Face Transformers, ChromaDB, NLTK; core Python tooling (Pandas, NumPy, Matplotlib); OpenAI API; LangChain, LangGraph, LangFuse for agentic RAG and LLMOps. Full-stack/data tech where it counts: FastAPI, React/Next.js, Elasticsearch, PostgreSQL, Docker, Redis, WebSocket—and cloud foundations on AWS (RDS Custom, FSx/EFS, S3/Glacier, Transfer Family). Reputation for raising engineering standards—performance, observability, data governance—and translating strategy into outcomes: faster time-to-market, lower run-rate, and modern data products that unlock revenue. Current focus: operationalizing GenAI safely and at scale—retrieval-first architectures, evaluation & guardrails, cost/perf tuning, and roadmaps that integrate AI with existing data platforms.