I build production-grade AI systems powered by LLMs, RAG, and agentic AI, with a strong focus on designing reliable, scalable, and production-ready AI platforms.

My work centers around taking AI products from concept → architecture → evaluation → implementation → deployment, including multi-agent systems, tool-using agents, retrieval pipelines, LLM orchestration, and cloud-native AI infrastructure.

I also have a strong background in full-stack engineering and additional research/development experience in XR (AR/VR/MR).

• 🤖 Agentic AI & Multi-Agent Systems with tool calling, orchestration, memory, and human-in-the-loop workflows
• 🧠 LLM Applications using modern foundation models, structured outputs, function calling, and prompt orchestration
• 🔎 Production RAG Systems with embeddings, vector search, hybrid retrieval, reranking, metadata filtering, and evaluation
• 🔌 AI Agent Tooling & MCP for connecting agents with APIs, databases, enterprise systems, and external tools
• 📊 AI Evaluation & Observability for measuring retrieval quality, agent behavior, reliability, latency, and failures
• ☁️ Production AI Platforms with scalable APIs, containers, event-driven workflows, monitoring, and CI/CD
• 🌐 Full-Stack Applications integrating AI systems with modern web interfaces and backend services

Python • TypeScript • JavaScript • Go • C# • C++

LLMs • Generative AI • Agentic AI • Multi-Agent Systems RAG • MCP • Tool / Function Calling • LLM Orchestration Embeddings • Vector Search • Hybrid Search • Reranking Prompt Engineering • Structured Outputs • AI Evaluation Transformers • PyTorch • Vector Databases

FastAPI • Node.js • REST APIs • WebSockets Event-Driven Systems • Microservices • Distributed Systems PostgreSQL • Redis • Vector Databases

React • Next.js • TypeScript • JavaScript • Flutter

AWS • Azure • Docker • Kubernetes CI/CD • Terraform • PostgreSQL • Redis • Firebase Observability • Monitoring • Cloud-Native Architecture

Unity • Unreal Engine • OpenXR • Meta XR SDK

Currently focused on building and exploring:

Agentic AI • Multi-Agent Systems • Long-Running Agents • Advanced RAG • MCP • Agent Memory • Context Engineering • AI Evaluation • LLM Observability • Production AI Infrastructure

• 🎓 Google Scholar: https://scholar.google.com/citations?user=3Hsr7bcAAAAJ&hl=en
• 📧 Email: panchalsmit312000@gmail.com

⭐ Interested in building production AI systems, agentic applications, or scalable AI infrastructure? Feel free to connect or explore my work.