AI Engineer with less than a year in Deep Learning & Full-Stack Development
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Final-year Computer Science student with hands-on experience in AI/ML engineering, LLM orchestration, and full-stack development. Interned at Garuda Aerospace training YOLOv8 deep learning models on custom aerial datasets. My final-year project is an AI-powered railway booking assistant built with LangGraph, RAG, and LLMs, showcasing a focus on building production-ready machine learning systems and full-stack applications with measurable real-world impact.
Agni College of Technology
B.E · CSE
August 1, 2022 – June 30, 2026
Dharani Matric Higher Secondary School
HSC
June 1, 2021 – May 31, 2022
Ashoka Sishu Vihar Matric School
SSLC
June 1, 2019 – May 31, 2020
Garuda Aerospace
AI/ML Engineer Intern
February 1, 2026 – May 1, 2026
Chennai, Tamil Nadu, India
AI Legal Assistant - Transformer + RAG
January 1, 2026 – Present
Built an AI legal assistant using Transformer-based LLMs with Retrieval-Augmented Generation (RAG), reducing hallucination by grounding every response in retrieved legal documents. Designed a hybrid retrieval mechanism combining dense semantic search (embeddings) and sparse keyword retrieval for accurate matching of legal acts, sections, and citations. Built a document retrieval pipeline using FAISS vector database to fetch relevant legal context at inference time. Added citation-based outputs and confidence scoring so users can verify which legal source each answer comes from. Implemented legal document summarisation and contract risk analysis to automatically flag high-risk clauses. Exposed the backend via FastAPI REST endpoints for clean frontend integration.
Ticket booking - AI-Powered Railway Booking App
January 1, 2026 – Present
Developed a full-stack railway booking platform with a stateful AI assistant that autonomously searches trains, checks live seat availability, and completes bookings end-to-end. Built an AI orchestrator using LangGraph to handle complex, multi-step user intents via deterministic function calling, enabling reliable multi-turn booking flows. Integrated a RAG pipeline using Google Gemini Embeddings and MongoDB Atlas Vector Search to ground AI responses in official railway policy documents, ensuring factual answers on refunds and luggage limits. Implemented Redis distributed locks to eliminate double-booking race conditions and Redis caching to reduce MongoDB query load significantly.
Second Place in Poster Presentation at college technical symposium.
Unknown
June 1, 2026 – Present
Python for Data Science
Great Learning
June 1, 2026 – Present
React.js
GeeksforGeeks
June 1, 2026 – Present
Anthropic Academy - Claude AI Full Track
Anthropic Academy
June 1, 2026 – Present
JavaScript
Udemy
June 1, 2026 – Present
React Native
GeeksforGeeks
June 1, 2026 – Present
Presented a research paper at an International Conference hosted by Gojan School of Business and Technology & Gojan College of Teacher Education.
Gojan School of Business and Technology & Gojan College of Teacher Education
June 1, 2026 – Present
Top 10 finish at Inter-Level Hackathon - competed against teams from 6+ colleges.
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to applying AI/ML concepts to real-world problems (legal assistant, railway booking). The internship experience shows adaptability (shifting project scope) and a structured approach to ML development. Participation in hackathons and research paper presentations indicates a drive for continuous learning and engagement with the technical community, which aligns well with an innovative and growth-oriented culture. The breadth of technologies used across projects (LLMs, RAG, Computer Vision, full-stack development) suggests a versatile and curious individual.
Soft Skills & Operational Fit
The candidate lists management skills, creativity, teamwork, problem-solving, critical thinking, leadership, time management, and active listening. These indicate a potential for good operational fit and collaboration within a team. The project descriptions also suggest an ability to work on complex problems and manage project scope changes.