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AI Engineer with less than a year in Python and Gen AI application development.
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Generative AI enthusiast with strong foundations in Python, Gen AI application development. Experienced in building Retrieval-Augmented Generation (RAG) solutions using LangChain, Pinecone, Vector Embeddings, and Large Language Models. Skilled in document processing, semantic search, prompt engineering, and developing AI-powered question-answering systems. Adept at learning new technologies quickly and applying them to solve business problems. Eager to contribute to the design and development of scalable GenAI solutions while continuously expanding expertise in LLMs, Agentic AI, and intelligent automation.
Pachaiyappa's College
Bachelor of Commerce · Corporate Secretaryship
August 1, 2020 – June 30, 2023
Enterprise Knowledge Assistant (RAG-Based AI Chatbot)
June 27, 2026 – Present
Developed a Retrieval-Augmented Generation (RAG) application that enables users to query enterprise documents using natural language and receive context-aware responses. Built a document ingestion pipeline to process PDFs, Word documents, and text files, including document chunking, metadata extraction, and vector embedding generation. Implemented semantic search using Pinecone Vector Database and LangChain to retrieve relevant document context and improve response accuracy. Designed and developed REST APIs using FastAPI for document upload, indexing, chat interactions, and knowledge base management. Integrated Large Language Models (LLMs) to generate accurate responses grounded in retrieved documents, reducing hallucinations and improving answer relevance. Implemented conversation memory and chat history management to support multi-turn interactions and enhance user experience. Optimized system performance through Redis caching, reducing response latency for frequently asked queries. Applied prompt engineering techniques to improve answer quality, response consistency, and contextual understanding. Implemented logging, exception handling, and input validation to ensure application reliability and maintainability. Enabled users to retrieve information from large document repositories efficiently, significantly reducing manual search effort and improving knowledge accessibility.
Expense Tracker API
June 27, 2026 – Present
Developed full CRUD operations (Create, Read, Update, Delete) with FastAPI endpoints for managing expenses; designed clean REST architecture with proper HTTP status codes. Implemented dynamic filtering and sorting by date, category, and ID using SQLAlchemy query builders; PUT API for partial field updates via PATCH/PUT operations. Applied input validation using Pydantic models; handled edge cases with proper 404 responses for invalid IDs; integrated FastAPI's HTTPException for consistent error messaging. Used SQLAlchemy ORM for efficient data handling with proper relationships and transactions; built scalable schema supporting multiple expense categories and date-based queries.
View ProjectLibrary Management System API
June 27, 2026 – Present
Implemented JWT-based auth with 3-strike account lockout (30-second window), passed OWASP security checklist. Enforced student/admin permissions at database layer; students auto-limited to 3 concurrent books, 7-day borrow window. Automatic fine calculation for overdue returns using SQLAlchemy service functions; Pydantic v2 validators rejected invalid data at API boundary. Separated concerns into dedicated modules (crud, crud_book, borrow_crud, schemas, models), enabling independent feature development and testing.
View ProjectPython Development Certification
BIX IT Academy
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects show a strong focus on AI/ML and API development, which aligns well with an AI Engineer role. The diversity of projects (RAG chatbot, expense tracker, library management) indicates a broad interest in applying technical skills to different problem domains. The self-driven learning in Generative AI and LLMs further supports a proactive and growth-oriented mindset, which is beneficial for cultural fit in an innovative environment. However, the lack of professional experience beyond a certification and a brief mention of TCS BFSI work makes it challenging to fully assess cultural adaptability in a team setting.
Soft Skills & Operational Fit
The candidate demonstrates an eagerness to learn new technologies quickly and apply them to solve business problems, which is a positive indicator for operational fit. The project descriptions highlight attention to detail in error handling, input validation, and modular architecture, suggesting a methodical approach to development. However, without direct experience or psychometric test results, it's difficult to fully assess collaboration, stress handling, or leadership potential.