AI Engineer focused on building reliable Generative AI applications, RAG systems, AI-agent workflows, and cloud-deployed products.
- Enterprise Generative AI workflows for process automation
- Retrieval-Augmented Generation (RAG) systems with Azure AI Search and vector databases
- AI agents using LangChain, LangGraph, FastAPI, and Model Context Protocol (MCP)
- Microsoft Teams and Microsoft 365 Copilot integrations
- Developer tools and code intelligence platforms
A multi-repository code intelligence platform for grounded Q&A across GitHub source code and documentation.
Stack: Rust, TypeScript, Next.js, Qdrant, Valkey, PostgreSQL, GitHub App, Docker, Gemini API
An enterprise Generative AI solution that transforms business-process catalogs into process maps, test cases, project timelines, and training materials.
Stack: Python, FastAPI, Azure AI Search, Azure App Service, Azure Storage, Docker, OpenAI API, Gemini API
An AI-powered application for multi-source news analysis, including sentiment classification, topic extraction, categorization, and summarization.
Stack: Python, CrewAI, Gemini API, Streamlit
AI / LLM: RAG, LangChain, LangGraph, Azure AI Search, OpenAI API, Gemini API, MCP, Vector Search, Qdrant, Pinecone
Backend: Python, FastAPI, Node.js, REST APIs, WebSockets
Frontend: TypeScript, React, Next.js, Tailwind CSS
Cloud / DevOps: Microsoft Azure, Azure App Service, Azure Container Apps, Azure Storage, Docker, GitHub Actions, CI/CD
Databases: PostgreSQL, MySQL, MongoDB, Valkey