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Achievements

Achievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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avigoen/README.md

Hi, I’m Avinash Goen 👋

🚀 AI Engineer | Generative AI & Agentic Systems | RAG | Full-Stack AI Builder

I build production-ready Generative AI systems that solve real enterprise problems — from multi-agent AI platforms to scalable RAG pipelines and AI-powered full-stack applications.

My work sits at the intersection of AI research, engineering, and product, turning ideas into systems that deliver measurable business impact.

🧠 What I Do

  • 🤖 Generative AI & LLM Systems

    • Multi-agent architectures (planner / executor / validator)
    • Retrieval-Augmented Generation (RAG)
    • Intent recognition & conversational AI
    • Token-efficient, cost-aware pipelines

  • 🏗 AI Engineering

    • Azure OpenAI, Mistral, open-source LLMs
    • Evaluation, monitoring, and optimization
    • Scalable, production-grade deployments

  • 🌐 Full-Stack AI Products

    • Backend: Python, Node.js, REST APIs
    • Frontend: ReactJS
    • End-to-end AI product delivery

🏆 Impact Highlights

  • 📉 Built a Generative AI Employee Self-Service Assistant

    • Reduced HR ticket escalations by 65%
    • Designed and deployed 10+ multi-agent enterprise solutions

  • ⚙ Architected agent-based workflows

    • ~2500 tokens end-to-end per workflow
    • High-accuracy intent routing and task execution

  • 🚀 Accelerated feature delivery by 30%

  • 💰 Improved performance and reduced cloud costs across AI systems

🛠 Tech Stack

Languages
Python · JavaScript

AI / ML
LLMs · Generative AI · RAG · NLU · Deep Learning · Agentic AI

Frameworks & Tools
Azure OpenAI · Mistral · LangChain · Vector Databases · FastAPI

Frontend & Backend
ReactJS · NodeJS · REST APIs

Cloud
Azure · AWS

📚 Background

  • AI Engineer / Data Scientist building enterprise-scale AI systems
  • Experience across research → product → deployment
  • Education:
    • 🎓 MS in Artificial Intelligence (ongoing)
    • 🎓 PG in AI & Data Science
    • 🌏 International immersion at NTU Singapore

📄 Publications

  • Predicting occupant thermal comfort for multiple air-side systems and seasonal scenarios using Autonomous HVAC CFD

🌍 Let’s Connect

💡 Dev Quote of the Day

⭐ I’m always interested in Generative AI, agentic systems, and impactful collaborations.

Pinned Loading

  1. Human_Profiler Human_Profiler Public

    Predict Human Gender, Age, Emotion and Similarity with a known celebrity using various Deep Learning methods

    Jupyter Notebook 1

  2. Konane_Checkers Konane_Checkers Public

    Game Engine to run Konane Checkers

    Python

  3. NLP_ConversationAI_AIsKitchen NLP_ConversationAI_AIsKitchen Public

    Conversation AI to read out Recipe and answer queries using NLP

    Python