Lead Gen AI Architect | Agentic AI | RAG | Multi-Agent Orchestration | LLM Systems | Vector Databases | Embedded AI
For the last 25+ years, I’ve worked across distributed systems, data engineering, machine learning, and now Agentic AI. From handling billion-node environments at LinkedIn and Yahoo! to building LLM-powered workflows, my focus has always been solving complex engineering problems under real-world constraints.
Currently working as Lead AI Engineer at Ninternet, where I work on Agentic AI systems involving RAG pipelines, multi-agent coordination, vector databases, evaluation workflows, and AI-powered automation. Recent contributions include reducing hallucinations by nearly 20%, improving productivity through AI-assisted development, and handling AI-driven DevOps and ML workflow optimization in fast-paced delivery environments.
Over the years, I’ve worked across Big Data infrastructure, search systems, predictive analytics, embedded AI, and applied machine learning while continuing independent research in computational mathematics and statistical modeling.
🔹 Agentic AI & LLM Systems: RAG, Multi-Agent Orchestration, Prompt Engineering, AI Evaluation, Tool Calling
🔹 AI & Data Engineering: Python, SQL, Snowflake, ETL Pipelines, MLflow, Pandas, PyTorch
🔹 Infrastructure & Platforms: LangChain, LangGraph, LlamaIndex, Hugging Face, OpenAI API, Vector Databases
🔹 Embedded & Edge AI: TensorFlow Lite, ONNX Runtime, Computer Vision, ROS2, SLAM
🔹 Certifications: Stanford Machine Learning Specialization | AWS & GCP Cloud Computing | Deep Learning Fundamentals
Open to opportunities in Gen AI Architecture, AI Transformation, Agentic Systems, and advanced engineering leadership.
Work Terms
Flexible work timings.