Generative AI Engineer with less than a year in LLM Applications & RAG.
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Recent MCA graduate with hands-on experience building Generative AI applications to address real-world business chal-lenges. Experience in building LLM-powered products using FastAPI, Flask, Gemini API, ChromaDB, and transformer-based NLP workflows. Optimized token usage and response latency to enhance AI application efficiency. Focused on building reliable and production-ready AI products.
Graphic Era University
Master of Computer Applications · Computer Applications
August 1, 2024 – June 30, 2026
Graphic Era University
Bachelor of Computer Applications · Computer Applications
August 1, 2021 – June 30, 2024
IntelliDoc AI Powered Adaptive Assessment Platform with RAG
March 1, 2026 – May 1, 2026
Asynchronous REST APIs for document upload, topic extraction, questions generation using FastAPI. Developed an automated document ingestion pipeline supporting PDF and DOCX files to convert documents exceeding 50 pages into 150 to 300 semantic segments per session. Improved the response relevance by developing a RAG pipeline based on semantically retrieving and constructing prompts for AI-generated educational content. Developed a downloadable questions PDF using ReportLab from document upload to export.
View ProjectAI Learner Buddy AI-Powered Learning Platform
June 1, 2025 – September 1, 2025
Built an AI learning platform that leverages the Gemini API to generate structured courses, chapter outlines, and educational materials for any given topic. Designed a course management system using SQLite for persistent storage of content, organization of courses, and efficient retrieval of learning data. Implemented secure login & registration features with password hashing, session-based authentication and server-side validation. Improved prompt engineering workflows to reduce token usage by 30% and decrease API response latency by 25.
View ProjectFake News Detection NLP Classification System
November 1, 2024 – December 1, 2024
Built a comprehensive NLP classifier pipeline consisting of text processing, feature extraction, model training, and evaluation using a 87.74% accuracy. Fine-tuned DistilBERT for fake news detection and compared the performances against SVM, Random Forest, XGBoost and Logistic Regression model. Model performance was assessed by Precision, Recall, F1-score and confusion matrix to determine classification strengths and weaknesses.
View ProjectAWS Artificial Intelligence Practitioner Learning Plan
AWS
October 1, 2025 – Present
AWS Cloud Essentials Knowledge Badge
AWS
October 1, 2025 – Present
Web Development using React JS
Robotronix India, Cognizance IIT Roorkee
March 1, 2023 – Present
Cultural Fit Analysis
The candidate's projects are highly aligned with the Generative AI Engineer role, demonstrating a clear passion and focus on AI/ML. The academic background and project diversity (RAG, AI learning platforms, NLP classification) show a broad interest within AI. However, the lack of professional experience and team-based projects might indicate a need for mentorship in a collaborative, fast-paced industry environment. The certifications in AWS AI and Cloud Essentials further support a proactive learning attitude.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex technical challenges independently, focusing on practical application and optimization (e.g., reducing token usage, improving response latency). The academic nature of projects suggests a strong learning aptitude and foundational understanding, but lacks evidence of collaborative, cross-functional team experience or handling production-level incidents.