AI Engineer with less than a year in RAG Pipelines & Generative AI
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AI & Data Science Engineer with hands-on experience building production-ready ML, NLP, and Generative AI systems. Proficient in RAG pipelines, LLM integration, vector search (FAISS), and full-stack Python development. Completed 7-month Infosys engineering program; delivered 2 end-to-end AI projects using LangChain, Hugging Face, and Streamlit. Eager to contribute scalable AI solutions at a growth-oriented organization.
Guru Tegh Bahadur Institute of Technology (GGSIPU)
B.Tech · Artificial Intelligence & Data Science
August 1, 2021 – June 30, 2025
Disha Delphi Global Sr. School
Senior Secondary (Class XII) · Science (Non-Medical)
N/A – May 31, 2019
MB International School
Secondary (Class X)
N/A – May 31, 2017
Infosys
System Engineer Trainee
November 1, 2025 – May 1, 2026
India
AI Document Assistant
June 24, 2026 – Present
Engineered a Retrieval-Augmented Generation (RAG) pipeline using Llama3, LangChain, and FAISS; supports PDF files up to 100 pages with average query response under 3 seconds. Integrated PyPDF2 for text extraction and FAISS vector indexing for similarity search across 10,000+ text chunks, achieving 90%+ answer relevance in testing. Built conversational memory with multi-turn context tracking via Streamlit, enabling follow-up questions without losing session context.
View ProjectAnime Recommendation System
June 24, 2026 – Present
Developed a Flask web app using Sentence Transformers (all-MiniLM-L6-v2) and FAISS to deliver description-based anime recommendations, processing a corpus of 5,000+ titles. Implemented MySQL user preference storage and session tracking; reduced cold-start recommendations by 40% through profile-based filtering. Integrated external anime metadata API with secure key management and rate-limiting for production stability.
View ProjectData Scientist Industrial Training & Internship Program
DevTown
May 1, 2023 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest and practical experience in AI/ML, which aligns well with an AI Engineer role. The diversity of projects (RAG system, recommendation system) and the full-stack training indicate a broad technical curiosity and willingness to learn across different domains. The academic background in AI & Data Science further reinforces this alignment. However, the experience level is entry-level, which might require more mentorship in a senior role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex technical challenges, manage project scope (e.g., PDF size limits, query response times), and integrate various technologies. The Infosys training suggests a structured approach to learning and problem-solving. However, without direct interview data, specific soft skills like teamwork, leadership, or adaptability cannot be fully assessed.