I’m Pankaj Kumar, an AI / ML Engineer and B.Tech Computer Science & Engineering (Data Science) graduate focused on turning data and AI ideas into usable, measurable, deployable products.

My engineering path: Data Science → Machine Learning → Deep Learning → Generative AI → RAG → Agentic AI → Multimodal AI → Production AI Engineering.

I build across the stack — from data preparation, model/LLM integration and retrieval to agents, APIs, databases, AI-powered websites and cloud deployment.

• 🤖 AI Engineering: Generative AI, LLM applications, RAG, Agentic AI, Multi-Agent Systems
• 📈 Data Science & Analytics: Python, SQL, EDA, Pandas, NumPy, Power BI, Tableau
• 🧩 AI Application Development: Streamlit, REST APIs, FastAPI, Flask, Django, React.js, Node.js
• 🔎 Retrieval: FAISS, ChromaDB, embeddings, semantic search, Sentence Transformers
• 👁️ Computer Vision: YOLOv8, OpenCV, PyTorch, multimodal AI
• ☁️ Deployment: Docker, IBM Cloud, GitHub Pages, AWS basics
• 💼 Current role: AI/ML Engineer Intern at TheSmartBridge, Noida
• 🎯 Open to: AI/ML Engineer, GenAI Engineer, RAG Engineer, AI Application Engineer, Full-Stack AI Engineer

                           ┌─────────────────────────────┐
                           │       🚀 AI PRODUCT         │
                           │  AI App • Website • Tool    │
                           └──────────────┬──────────────┘
                                          │
            ┌─────────────────────────────┼─────────────────────────────┐
            │                             │                             │
            ▼                             ▼                             ▼
   ┌────────────────┐          ┌────────────────┐          ┌────────────────┐
   │ 🔎 RAG SYSTEMS │          │ 🤖 AI AGENTS   │          │ 👁️ MULTIMODAL │
   │ Ingest         │          │ Plan           │          │ Text           │
   │ Chunk          │          │ Reason         │          │ Image          │
   │ Embed          │          │ Tools / MCP    │          │ Video          │
   │ Retrieve       │          │ Memory         │          │ Audio          │
   │ Generate       │          │ Execute        │          │ Vision         │
   └───────┬────────┘          └───────┬────────┘          └───────┬────────┘
           │                            │                            │
           └────────────────────────────┼────────────────────────────┘
                                        ▼
                           ┌─────────────────────────────┐
                           │ 🧩 AI ENGINEERING LAYER     │
                           │ Python • LLMs • APIs • DBs  │
                           │ FastAPI • Flask • Django    │
                           └──────────────┬──────────────┘
                                          │
                              ┌───────────┴───────────┐
                              ▼                       ▼
                    ┌──────────────────┐   ┌────────────────────┐
                    │ ☁️ Cloud / Deploy │   │ 📊 Data / Analytics│
                    │ Docker • AWS     │   │ SQL • BI • EDA     │
                    └──────────────────┘   └────────────────────┘

Logo badges below use the Simple Icons logos so the tools appear with their recognizable technology marks instead of text-only badges.

An AI-enabled herbal knowledge platform combining plant recognition, digital AYUSH knowledge, voice interaction and full-stack development.

🔗 View ECHO Repository

flowchart LR
    A[📄 Documents] --> B[📥 Ingestion]
    B --> C[✂️ Chunking]
    C --> D[🧠 Embeddings]
    D --> E[(🔎 Vector DB)]
    F[👤 User Query] --> G[🧠 Query Embedding]
    G --> E
    E --> H[📚 Relevant Context]
    H --> I[🤖 LLM]
    I --> J[✅ Grounded Response]
    J --> K[🔗 Citations]

flowchart LR
    A[🎯 User Goal] --> B[🧭 Planner]
    B --> C[🤖 Agent / Reasoner]
    C --> D{🧩 Tool Needed?}
    D -->|Yes| E[🔌 Tool / API / MCP]
    E --> C
    D -->|No| F[🧠 Memory + Context]
    F --> G[✅ Final Response]

flowchart TB
    UI[🌐 Web / Streamlit / React UI]
    API[⚙️ FastAPI / Flask / Django]
    AI[🤖 ML / LLM / RAG / Agents]
    DATA[(🗄️ SQL / MongoDB / Vector DB)]
    CLOUD[☁️ Docker / Cloud Deployment]

    UI --> API
    API --> AI
    AI --> DATA
    API --> DATA
    API --> CLOUD

May 2026 – Present · Noida

• Building GenAI applications using LLMs, RAG, LangChain, LangGraph and AI agents.
• Developing end-to-end ML workflows from preprocessing and feature engineering through evaluation and deployment.
• Working with vector databases, REST APIs, cloud tooling and technical documentation.
• Contributing to AI/ML knowledge transfer, project demonstrations and enterprise-oriented technical work.

Worked across internships and training involving Python, SQL, EDA, data preprocessing, predictive modelling, ML pipelines, NLP/LLM applications, Power BI and full-stack AI applications.

B.Tech — Computer Science & Engineering (Data Science)
Shri Ramswaroop Memorial College of Engineering & Management, Lucknow
2022–2026 · CGPA 8.78/10 · Branch Topper

Selected areas include:

• 🤖 AI Agents for Beginners — Simplilearn
• 🧠 Machine Learning with Python — IBM
• ☁️ AWS APAC Solutions Architecture — Forage
• 📊 Data Science / ML internships and simulations
• 🛰️ Application of Space Technology — IIRS / ISRO
• 🔐 Saviynt Identity Security for AI Age
• 🌐 AICTE / Edunet technical programs
• ☁️ Google Cloud / Generative AI learning
• 🔬 IBM Cloud and Big Data learning

📊 Data Analytics
       │
       ▼
🧠 Machine Learning
       │
       ▼
🔬 Deep Learning
       │
       ▼
✨ Generative AI
       │
       ▼
🔎 RAG Systems
       │
       ▼
🤖 Agentic AI
       │
       ▼
🧩 Multi-Agent Systems
       │
       ▼
👁️ Multimodal AI
       │
       ▼
🚀 Production AI Engineering

Advanced RAG architectures • Agentic AI & multi-agent systems • MCP and tool-connected AI • LLM evaluation • AI memory architectures • Multimodal AI • Production-grade AI APIs • Cloud deployment • Scalable AI systems • AI system design

Python • Machine Learning • Generative AI • RAG • LangChain • LangGraph • LLMs • AI Agents • Vector Databases • Computer Vision • FastAPI • Flask • Django • SQL • Power BI

🚀 Building practical AI systems from data → intelligence → product.