AI Engineer with less than a year in LLMs & RAG, skilled in Backend Development and DevOps.
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Final-year Computer Science student at BRAC University building AI systems that ship, from retrieval pipelines to automated assessment tools. I've owned backend AI work across LLMs, Docker, CI/CD, and production deployments, including systems used by 50-100 users and a move from a static Linux host to DigitalOcean App Platform.
BRAC University
Computer Science
September 1, 2022 – September 1, 2026
FlyRank AI
Backend AI Engineering - internship
June 1, 2026 – Present
Dhaka, Dhaka Division, Bangladesh
Data Solution-360
AI & DevOps Engineering - internship
January 1, 2026 – April 1, 2026
Dhaka, Dhaka Division, Bangladesh
BRAC University
Junior Executive, Press Release & Publications
September 1, 2022 – September 1, 2024
Dhaka, Dhaka Division, Bangladesh
ClientManager Pro - AI-Powered MERN Client Management System
August 1, 2025 – September 1, 2025
A MERN client management platform with role-based access, project workflows, live chat, and document generation. Designed a multi-role system with Admin, Client Manager, and Client views, plus route guards, middleware auth, and isolated dashboards. Ingests GitHub repositories via gitingest and generates local embeddings with Transformers.js using all-MiniLM-L6-v2, with no external embedding API calls. Stores embeddings in Pinecone and generates answers with Google Gemini 1.5 Flash, cutting redundant reads through embedding cache, answer cache, and query deduplication. Includes SRS auto-generation from proposals, PDF contract generation, Socket.io live chat, JWT auth, and a dual-feedback flow after projects.
View ProjectData-Aware RAG System for Research Papers
October 1, 2023 – December 1, 2023
A research-paper search tool built around PDF ingestion, structured table extraction, and hybrid retrieval across vector and BM25 indices. Processes PDFs and extracts tables into DuckDB for structured retrieval. Uses vector search plus BM25 to route queries across multiple retrieval paths. Adds a Streamlit UI, DAG orchestration, async ingestion, and 3-tier caching from embeddings to answers. Reached 400x query speedup, from about 2000ms to 5ms, with answer caching.
View ProjectCultural Fit Analysis
The candidate's academic projects and internship experiences align well with an AI Engineer role, showcasing a strong interest and practical application in the field. The diversity of projects (RAG, MERN with AI, MCQ pipeline) indicates adaptability and a broad skill set. The involvement in university clubs suggests a willingness to collaborate and contribute beyond core technical tasks.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and system optimization. The experience with a multi-agent MCQ pipeline suggests an understanding of complex system design and iterative improvement. The role as Junior Executive also hints at communication and organizational skills, though these are not directly assessed in a technical context.