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Focusing
🎯
Focusing
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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 am 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 using Azure OpenAI, Azure AI Search, and Semantic Kernel.

At T-Mobile (via IBM): led a 18-person cross-platform engineering team building Arrow, T-Mobile's enterprise design system across web, iOS, Android, and AEM. Also led the GitHub Copilot rollout to 5,000+ developers value stream mapping, training workshops, prompt engineering programs, and automated onboarding infrastructure.

Outside of enterprise work, I built the complete React frontend for Gexbot a live options analytics platform with real-time WebSocket data streaming serving a large and growing trading community.

I'm a hands-on lead comfortable going deep on architecture, shipping code, and running teams. 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 traders. Implemented live gamma exposure charts using WebSockets for continuous market-hours data streaming. Architected the full state layer in Redux for V1, then led a complete refactor to Zustand for the production version — improving performance and reducing bundle complexity.
  • Ideal For: Anyone interested in real-time financial data visualization, WebSocket-driven UIs, or React state management at scale.
  • Live Site: gexbot.com

🧠 RAG Demo Solution (Updated 2025)

  • Description: A C#/.NET Azure Functions & Semantic Kernel demo that ingests documents, leverages Azure OpenAI & Azure AI Search for Retrieval-Augmented Generation, and powers an agent-based chat API.
  • Ideal For: Developers building context-aware conversational AI and hybrid search pipelines.
  • GitHub Repository: AI RAG Chatbot 2025

🤖 LinkedIn AI Auto Poster

  • Description: An intelligent, AI-driven solution designed to automate the creation and publishing of engaging LinkedIn content. Leveraging Azure OpenAI technology, this application streamlines content generation and ensures consistent, high-quality posting directly to LinkedIn.
  • Ideal For: Professionals looking to enhance their digital presence effortlessly while saving time and maintaining active audience engagement.
  • 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 TanStack Remix 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

    Use Ai to Post to Linkedin at 9am every morning.

    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