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amit User

@amit_yadav

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Full-stack developer building AI-powered web apps with React, Node.js, and LLM/RAG integrations.

India

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What I'm looking for

I’m looking for a full-stack role where I can build production web apps end-to-end and integrate LLM/RAG features. I value clean, maintainable code, ownership, and fast iteration with real user feedback.

I’m a final-year B.Tech student with hands-on experience building and shipping full-stack web applications from scratch. I work across the entire development cycle—designing REST APIs, wiring up React frontends, managing MongoDB databases, and deploying containerized services on cloud platforms.

My recent projects blend traditional web development with AI integration, including RAG pipelines and LLM-powered features using Groq and OpenAI APIs. I write clean, maintainable code, take ownership of what I build, and iterate quickly—improving prompt logic, latency, and API reliability through real-session testing and production feedback.

Experience

Work history, roles, and key accomplishments

Enterprise CRM Developer

Gharpayy CRM

Built a full-stack enterprise CRM from scratch covering lead management, pipeline stage tracking, conversion analytics dashboards, and automated follow-up scheduling via cron jobs. Optimized MongoDB Atlas queries with proper indexing to significantly reduce dashboard load times and implemented reusable Chart.js components for revenue and pipeline visualizations.

MongoDB Atlas Chart.Js REST APIs Data Modeling Query Optimization Data Visualization

AI Journal Platform

AI Journal System

Shipped a production journaling platform that generates sentiment scores and plain-English summaries per entry using Llama 3.1. Secured the backend by moving API keys server-side and added rate limiting; reduced average LLM API response time by 25% via request batching and prompt caching, and containerized the stack with Docker for reproducible deployments.

MongoDB Docker API Security Rate Limits Prompt Engineering

Full-Stack AI Interview Simulator

PrepWise AI

Built a full-stack AI interview simulator where users upload resumes and receive role-specific questions generated via a RAG pipeline using Llama 3.3-70B on Groq, with real-time rubric-scored answers. Designed the Express REST API layer with PDF parsing (Multer), vector context retrieval, and streamed LLM responses; deployed on Vercel with MongoDB-backed session state.

REST APIs MongoDB GROQ PDF Parsing Llama 3.3 70B Recharts LLaMA 3.3 70B

Education

Degrees, certifications, and relevant coursework

Puducherry Technological University

Bachelor of Technology, B.Tech

2023 -

Pursuing a B.Tech at Puducherry Technological University (final-year), with coursework including Data Structures & Algorithms, Operating Systems, DBMS, and Computer Networks.