I build practical AI systems that connect large language models with reliable data, business workflows, and backend services. My focus includes retrieval-augmented generation, AI copilots, agentic workflows, text-to-SQL applications, and production-oriented automation.

• 🤖 I build LLM-powered applications, retrieval pipelines, and AI copilots.
• 🐍 I develop Python APIs and backend services for practical AI products.
• 🔎 I work with RAG, hybrid retrieval, embeddings, prompt engineering, and guardrails.
• 📚 I am exploring agentic AI, LangGraph, MCP, and evaluation workflows.
• ✅ I bring a strong software testing and automation mindset to AI application quality and reliability.

• Languages: Python, TypeScript, JavaScript, SQL
• AI/LLM: LLM applications, RAG, embeddings, prompt engineering, NLP, AI agents, LangGraph, MCP, text-to-SQL
• Backend: FastAPI, REST APIs, Next.js, SQLAlchemy
• Data: PostgreSQL, SQLite, ChromaDB, BM25, Sentence-Transformers
• Cloud & Tools: AWS, GCP, Docker, Linux, Git, GitHub Actions, VS Code

A modular HRMS platform covering employee lifecycle management, attendance, leave, payroll, and ticketing. Its full-stack architecture provides a foundation for AI copilots and workflow automation across HR operations.

Built with: FastAPI, Next.js, Docker, SQLAlchemy, PostgreSQL

A document-based healthcare RAG chatbot designed for secure knowledge access. It combines role-based access control, sensitive-content filtering, and hybrid retrieval to produce context-aware answers from trusted documents.

Built with: Python, FastAPI, OpenAI API, BM25, Sentence-Transformers, SQLite

A text-to-SQL analytics platform that allows users to query business data in natural language. It uses schema-aware validation, guardrails, and read-only execution to support safer self-service analytics.

Built with: Python, FastAPI, Claude Sonnet 5, ChromaDB, SQLite, Next.js, TypeScript

• 🧩 Building AI copilots and intelligent workflow automation.
• 🔐 Designing secure RAG systems and retrieval pipelines.
• 📈 Improving reliability, evaluation, and production readiness for AI applications.
• 🕸️ Exploring agentic AI, prompt engineering, and MCP-based workflows.
• 📝 Sharing practical AI engineering projects and technical learnings.