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AI Engineer with less than a year in LLM agents, RAG, and Python.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
B.E graduate in Al & Machine Learning with hands-on experience building LLM agents, RAG pipelines, and REST APIs using Python, LangChain, and FastAPI. Familiar with LLM APIs, Hugging Face, prompt engineering, and GenAl workflows. Experienced with vector databases and SQL.Eager to contribute to Al automation and Generative Al solutions as a fresher, with a strong willingness to learn and grow.
University of Mumbai
B.E. · Artificial Intelligence & Machine Learning
August 1, 2022 – June 30, 2026
Ramnarain Ruia College, Mumbai
HSC (Class XII)
June 1, 2020 – May 31, 2022
I.E.S Bhandup, Mumbai
SSC (Class X)
June 1, 2010 – May 31, 2020
AI Research Agent
June 24, 2026 – Present
Built an LLM-powered agent that searches, retrieves, and summarizes research information on its own. Added tool-use support so the agent can call external APIs and web sources during a query. Kept the architecture modular with clear separation between agent logic, tools, and prompt handling for easier maintenance.
View ProjectRAG-Based Document Question Answering System
June 24, 2026 – Present
Built a document ingestion and retrieval pipeline using FAISS for semantic search. Connected an LLM API to generate answers based on the retrieved content from uploaded documents. Created a Streamlit UI that lets users upload files and ask questions interactively.
View ProjectBook Management REST API
June 24, 2026 – Present
Developed a CRUD REST API using FastAPI for managing a book dataset stored in JSON format. Used Pydantic for schema validation and structured data models covering title, author, genre. Leveraged FastAPI's auto-generated Swagger UI for easy testing and documentation.
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate initiative and a strong interest in cutting-edge AI technologies, aligning well with an innovative and growth-oriented culture. The diversity of projects (LLM agents, RAG, REST APIs) shows a broad technical curiosity. As a fresher, the candidate's eagerness to learn and grow is a positive indicator for cultural integration.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to structure code modularly and consider maintainability, which suggests good operational fit. Participation in a college committee as 'Publicity Head' hints at organizational and communication skills, though direct evidence of professional soft skills is limited due to lack of work experience.