Computer Science graduate (2026) with a strong interest in Artificial Intelligence, Machine Learning, Generative AI, and LLM-powered application development.

I enjoy building practical AI applications using Python, LangChain, RAG, LLM APIs, vector databases, and FastAPI. My work includes knowledge retrieval systems, document intelligence applications, AI-powered research workflows, and API-based AI solutions.

Currently focused on strengthening my skills in Generative AI, Retrieval-Augmented Generation (RAG), LLM application development, AI agents, prompt engineering, and cloud-based AI systems while continuously improving my problem-solving and software engineering fundamentals.

• LangChain
• Retrieval-Augmented Generation (RAG)
• Large Language Models (LLMs)
• Prompt Engineering
• Embeddings & Semantic Search
• OpenAI API
• Gemini API

• Python
• Java
• SQL
• JavaScript

• FastAPI
• REST APIs
• Flask
• Spring Boot
• Node.js

• FAISS
• ChromaDB
• MySQL
• MongoDB

• AWS (EC2, S3, IAM)
• Docker
• Git
• GitHub
• Postman

• Artificial Intelligence & Machine Learning
• Generative AI
• Large Language Models
• Retrieval-Augmented Generation (RAG)
• AI Agents & LLM Applications
• Natural Language Processing
• Semantic Search & Vector Databases
• AI Backend Engineering
• Cloud-Based AI Applications
• Data Structures & Algorithms

Built a Retrieval-Augmented Generation (RAG) application using Python, LangChain, FAISS, and Gemini API for semantic document retrieval and context-aware question answering.

Developed an LLM-powered research assistant using Python, LangChain, OpenAI API, and FAISS to process research documents and dynamically route queries between document retrieval and direct LLM generation.

Built a FastAPI-based Generative AI application for extracting structured information from PDF documents using LLM APIs, with structured JSON responses and Docker-based deployment.

Developed an AI-powered knowledge retrieval system using RAG and semantic search to enable users to retrieve and interact with organizational knowledge efficiently.

Designed REST APIs with authentication, caching, database integration, and backend validation using Java and Spring Boot.

• AWS Certified Cloud Practitioner
• Co-Author of an IEEE Conference Publication on Digital Twin Technology
• Participated in the Incedo AI Hackathon and developed an AI-driven solution prototype
• Solved 250+ Data Structures & Algorithms problems across coding platforms

• Generative AI & LLM Application Development
• LangChain & RAG Pipelines
• AI Agents & Tool-Calling Workflows
• Vector Databases & Semantic Search
• Prompt Engineering
• FastAPI for AI Applications
• Cloud Deployment of AI Applications
• LLM Evaluation & Optimization

LinkedIn: www.linkedin.com/in/pujitha-mule-125790254

GitHub: github.com/pujitha-mule

Portfolio: pujitha-portfolio-smoky.vercel.app

Email: pujithamule06@gmail.com