Tech Stack

    Tools I build with

    01

    Languages

    • JavaScript
    • TypeScript
    • Python
    • Java
    • C

    02

    Frontend

    • React
    • Next.js
    • Vue
    • Tailwind

    03

    Backend & Data

    • Node.js
    • Express
    • PostgreSQL
    • MongoDB
    • Firebase

    04

    Tooling

    • Git
    • GitHub
    • NPM
    • Docker
    • Linux

    05

    Cloud & Infra

    • AWS
    • Google Cloud
    • Vercel
    • Nginx

    Experience

    My professional journey.

    Full Stack Developer

    ASSANJ
    May 2026 - Present
    • Developing and optimizing full-stack web applications using React, Node.js, and REST APIs; collaborating in an agile, industry-oriented environment to ship features across the complete development lifecycle.
    • Implementing scalable backend logic, responsive UI components, and streamlined CI/CD workflows for real-world client-facing products; contributing to code reviews and architectural decisions.
    ReactReact
    Node.jsNode.js
    GitGit
    GitHubGitHub
    DockerDocker

    Backend Developer

    Cestrum
    Jan 2026 - March 2026
    • Building UniTalks — an anonymous real-time chat platform with voice/video via WebRTC, designed to scale to 1,000+ concurrent connections.
    • Owned backend architecture around Node.js, Socket.IO, and Redis Pub/Sub for distributed session state; containerized services with Docker and deployed behind Nginx on AWS EC2.
    • Set up GitHub Actions CI/CD to cut deployment time by ~75%; load-tested the stack at 150+ concurrent users to validate performance under real traffic.
    Node.jsNode.js
    ReactReact
    DockerDocker
    AWSAWS
    NginxNginx
    GitGit

    Generative AI Intern

    Analytx4t
    Dec 2025 - Feb 2026
    • Built production GenAI applications using LLMs, LangChain, and Python; delivered 8 RAG pipelines for document intelligence with vector search and tool-augmented agents.
    • Reduced inference latency by 40% via chunking and embedding tuning; evaluated 5+ prompt strategies, boosting RAG faithfulness scores by 22% on internal benchmarks.
    PythonPython
    GitGit
    DockerDocker

    Projects

    • Published Patent

      System and Method for Stress and Pain Detection Using Multi-Scale Transformer-Based Neural Networks — Application No. 202641065281

    • RAG Chatbot

      Document-grounded Retrieval-Augmented Generation pipelines with LangChain, vector search, and LLMs — including production RAG work that cut inference latency by ~40%.

    • Ongoing Project — ResearchPilot

      AI-powered research intelligence platform combining fine-tuned LLMs, Retrieval-Augmented Generation (RAG), semantic search, and machine learning for paper analysis, abstract enhancement, statistical recommendations, and research gap discovery.

    LET'S WORK
    TOGETHER

    Contact Form

    Please contact me directly at dwivedivaibhav3110(at)gmail.com or drop your info here.

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    © 2026 Vaibhav Dwivedi. All rights reserved.