Hassan Jamal Khan

Built and deployed production-grade GenAI, LLM, RAG, and agentic AI systems using LangChain, LlamaIndex, and LangGraph. Developed graph-based RAG with semantic search using FAISS/Pinecone for enterprise applications. Engineered ML/DL pipelines in Python with PyTorch/TensorFlow and transformer-based approaches. Built scalable FastAPI microservices, Dockerized AI applications, and deployed cloud inference systems. Implemented MLOps and CI/CD pipelines using MLflow, Airflow, and Kubeflow for model lifecycle management, delivering solutions across telecom, banking, IoT, and enterprise automation use cases.

Developed and maintained Django web applications integrated with React front-ends. Designed and optimized SQL database schemas to improve performance and reliability. Automated Outlook email data ingestion using Python, transformed datasets with Pandas/NumPy based on business logic, and built reliable data processing workflows. Worked with a range of ML and NLP techniques (including scikit-learn, transformers, RNN/LSTM/GRU) and supported GenAI development using LangChain, RAG, fine-tuning, and quantization workflows. Supported production development with REST APIs, JWT authentication, Celery, Django channels, and deployment/infrastructure practices on AWS.

Built and deployed RESTful APIs using Django and PyMongo, automating workflows with Celery and Playwright to improve operational efficiency. Supported full-cycle development including design, implementation, testing, and deployment of backend services.