About Me

Hello! I'm Waleed, an AI Engineer passionate about building intelligent, real-world applications using Generative AI and Machine Learning. I enjoy solving complex problems and creating systems that think, learn and automate.

My expertise includes frameworks like LangChain, LangGraph, CrewAI and automation tools like n8n and Zapier. I work across RAG pipelines, AI agents, Prompt Engineering and Vector Databases to bring ideas to life.

I'm driven by curiosity and the potential of AI to improve how we work and interact with technology. If you'd like to connect or collaborate, feel free to reach out!

Technical Skills

Languages

  • Python
  • C++
  • SQL
  • JavaScript

AI Frameworks & Tools

  • LangChain
  • LangGraph
  • CrewAI
  • RAG Pipelines
  • Knowledge Graphs
  • Prompt Engineering
  • Fine-Tuning
  • Diffusion Models
  • TensorFlow
  • PyTorch
  • Ollama
  • FastAPI
  • Flask
  • Streamlit
  • React

Automation & Integration

  • n8n
  • Zapier
  • Make.com

Libraries

  • Pandas
  • NumPy
  • Matplotlib
  • Plotly
  • Scikit-learn

Databases

  • MongoDB
  • SQL Server
  • SQLite
  • Vector DBs (Qdrant, Chroma, FAISS, Weaviate, Pinecone, Neo4j)

Developer Tools

  • Git
  • Docker
  • Jupyter Notebook
  • Google Colab
  • VS Code
  • PyCharm
  • Postman

Cloud & MLOps

  • AWS (SageMaker, Bedrock, EC2, S3)
  • Docker
  • CI/CD Pipelines

Projects

Post Buddy

A content management tool integrating AI Agents, Qdrant, Next.js and Mongo DB for seamless post categorization and retrieval.

PythonLangChainAgentic AINext.jsQdrantRAGMongo DBFastAPI

Legal RAG System

A Retrieval-Augmented Generation (RAG) system based on Agentic AI for analyzing contractual documents using LangChain, LangGraph and Qdrant.

PythonGraphRAGLangGraphQdrantFlask

Face Anti-Spoofing Model

A ViT-based model to detect real vs. spoofed images, improving security in face recognition applications.

PythonDeep LearningFine-TuningPyTorchViT

Smart Summarizer

A chatbot-powered text summarizer that condenses lengthy documents into key insights using LangChain and RAG.

PythonLangChainRAGChromaStreamlit