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Achievements

Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: QuickdrawAchievement: Arctic Code Vault Contributor

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derekhuynen/README.md

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🚀 About Me

I'm a Senior AI and Full-Stack Engineer with 6+ years delivering enterprise-grade systems across AI, cloud, and product development. I specialize in Generative AI and RAG architecture: building document ingestion pipelines, AI chatbots, and intelligent search systems with Azure OpenAI, Azure AI Search, and Semantic Kernel.

At T-Mobile (via IBM) I lead an 18 person cross-platform engineering team building Arrow, T-Mobile's enterprise design system across web, iOS, and Android. Before that I led T-Mobile's enterprise GitHub Copilot rollout, growing adoption to roughly 6,000 developers, building automated access management, and running value stream mapping and training programs across the organization.

Outside of enterprise work, I built the complete React frontend for Gexbot, a real-time options-analytics platform with live WebSocket data streaming that serves a 10,000+ trading community.

I'm a hands-on lead, comfortable going deep on architecture, shipping code, and running teams. I'm currently looking to bring this to a product-focused company where I can build something that compounds over time.

🌟 Featured Projects

📈 Gexbot: Live Options Analytics

  • Description: Built the complete React frontend for gexbot.com, a real-time options-analytics platform for active stock and options traders. Implemented custom, data-dense charts and live gamma-exposure data streaming over WebSockets, and led the state-management refactor from Redux to Zustand for better performance.
  • Ideal For: Anyone interested in real-time financial data visualization, WebSocket-driven UIs, or React state management at scale.
  • Live Site: gexbot.com

🧠 AI RAG Chat Bot

  • Description: A keyless, scale-to-zero RAG chat app on Azure: streaming chat with clickable citations and image understanding over your own documents, deployable in one command. Azure Functions (.NET 10) + React, with hybrid (keyword + vector) retrieval and Managed Identity auth (no keys anywhere).
  • Ideal For: Developers building context-aware conversational AI, hybrid search, and keyless Azure architectures.
  • GitHub Repository: ai-rag-chat-bot

🔌 derekhuynen-mcp-server

  • Description: A production-grade reference Model Context Protocol (MCP) server in TypeScript: one transport-agnostic core serving tools, resources, and prompts over two transports (stdio and Streamable HTTP), backed by a validated data layer, a real test suite, Docker, and CI.
  • Ideal For: Developers building or templating their own MCP server with clean, testable architecture.
  • GitHub Repository: derekhuynen-mcp-server

🤖 LinkedIn AI Auto Poster

  • Description: An autonomous Azure pipeline that writes, illustrates, and ships LinkedIn posts on a schedule, with a Next.js dashboard to browse what it has shipped and watch it generate a sample post live.
  • Ideal For: Professionals looking to maintain an active digital presence while saving time.
  • GitHub Repository: linkedin-ai-auto-poster

💻 Tech Stack

Programming Languages

JavaScript TypeScript C# Python.Net

Frameworks & Libraries

React Node.js Next.js Material-UI Tailwind CSS Redux Redux Saga Zustand Semantic Kernel

AI Tools & Technologies

OpenAI AI Agents RAG GitHub Copilot MCP

Databases

Postgres Cosmos DB MongoDB SQLAI Search

Tools & Technologies

Docker Git FigmaAzure WebSockets

🏅 Certifications

  • Microsoft Azure AI Engineer Associate (AI-102)
  • Microsoft Azure AI Fundamentals (AI-900)
  • Microsoft Azure Fundamentals (AZ-900)
  • Microsoft Azure Data Fundamentals (DP-900)
  • Power Platform Fundamentals (PL-900)

📫 Contact Me

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  1. linkedin-ai-auto-poster linkedin-ai-auto-poster Public

    Autonomous Azure pipeline that writes, illustrates, and ships LinkedIn posts on a schedule. Azure Functions (TypeScript) + Next.js dashboard.

    TypeScript

  2. ai-rag-chat-bot ai-rag-chat-bot Public

    A serverless rag chatbot solution that uses Azure OpenAI, Azure AI Search, and Semantic Kernel to provide intelligent responses from your own data sources with accurate citations.

    C# 3