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AI Engineer with less than a year in LLM integrations & RAG systems.
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Assessing your cultural and operational fit
BCA graduate with hands-on experience building AI-powered applications using Python, LLM integrations, retrieval systems, and API development. Interested in applied machine learning, NLP systems, model optimization, and building production-ready AI applications. Looking to contribute to real-world AI products while expanding expertise in transformers, model serving, and evaluation workflows.
Annai College of Arts and Science
Bachelor of Computer Applications (BCA)
August 1, 2022 – June 30, 2025
Website RAG (Retrieval-Augmented Generation) Tool
January 1, 2024 – Present
Built a Retrieval-Augmented Generation pipeline for intelligent question answering using chunking and retrieval workflows. Developed backend API endpoints for AI workflows and structured inference requests. Simulated vector-based retrieval using chunking and context selection techniques. Evaluated response quality through prompt iterations and retrieval improvements to reduce hallucinations. Worked with structured JSON flows for LLM input/output handling.
View ProjectTask Management API System
January 1, 2024 – Present
Built a task manager web application using Flask with server-side rendering. Designed REST endpoints and backend workflows for CRUD operations. Implemented CRUD operations with SQLite database. Deployed the application on Render using Gunicorn.
View ProjectAI Resume Analyzer
January 1, 2024 – Present
Built an LLM-powered system for resume analysis and job matching. Built structured workflows for parsing PDFs and transforming unstructured input into model-friendly data. Tested prompt iterations to improve response quality and consistency. Integrated REST APIs for real-time AI response generation.
View ProjectDatabase Management
Meta
June 1, 2026 – Present
API Testing Path
Postman Academy
June 1, 2026 – Present
Problem Solving
Hacker Rank
June 1, 2026 – Present
Python for Everybody
University of Michigan
June 1, 2026 – Present
Google Cloud Gen AI Academy (APAC 2026)
Google Cloud Skills Boost
June 1, 2026 – Present
AI on AMD
AMD
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a clear focus on AI/ML applications, particularly LLM and RAG systems, which aligns well with an AI Engineer role. The certifications in Google Cloud Gen AI Academy and AI on AMD further indicate a proactive approach to learning and staying current with industry trends. The diversity of projects (RAG tool, resume analyzer, task manager) shows a breadth of application development, though all are academic. The 'Currently Learning' section also highlights a commitment to continuous professional development.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured workflows, iterate on solutions (prompt iterations), and integrate various technologies. The academic projects suggest a foundational understanding of software development lifecycle, including deployment (Render, Gunicorn). However, without direct work experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or broader work attitude.