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me-prakhargupta/README.md

Prakhar Gupta

Backend-focused Software Engineer building production-ready applications with Node.js, Express.js, MongoDB, Next.js, and TypeScript.

I enjoy solving backend engineering problems involving authentication systems, API design, data pipelines, background jobs, AI integrations, and production deployments.

Recent work includes building a career intelligence platform, an anonymous messaging platform, and an AI-powered journaling system.


Engineering Focus

  • Authentication & Identity Systems
  • Backend Architecture & API Design
  • Data Pipelines & Web Scraping
  • Background Jobs & Queue Processing
  • AI / LLM Integrations
  • Production Deployment & Debugging
  • Full-Stack Product Development

Tech Stack

Backend

Node.js • Express.js • MongoDB • Mongoose

Frontend

Next.js • React • Tailwind CSS

Languages

JavaScript • TypeScript

Tools & Infrastructure

Git • GitHub • Postman • Redis • BullMQ • Resend

Deployment

Render • Vercel


Featured Projects

Career intelligence platform that aggregates opportunities from multiple hiring sources and provides a personalized workspace for discovering, saving, and managing applications.

Highlights

  • Built a multi-source scraping and normalization pipeline
  • Designed a preference-based opportunity matching engine
  • Implemented JWT authentication, email verification, and password recovery workflows
  • Added application bookmarking and management workspace
  • Automated stale listing cleanup using MongoDB TTL indexes
  • Built notification infrastructure with Resend and background job processing

Privacy-first anonymous messaging platform designed around zero identity exposure, allowing users to communicate without revealing personal information.

Highlights

  • JWT authentication with access & refresh token architecture
  • Granular route-level rate limiting for abuse prevention
  • Centralized API error handling using custom abstractions
  • Modular service-oriented backend architecture
  • Production deployment and debugging across Vercel and Render

AI-powered journaling platform enabling users to perform on-demand emotion and keyword analysis using Google Gemini.

Highlights

  • Integrated Google Gemini for journal analysis
  • Implemented database-level response caching reducing token usage by ~40%
  • Designed an on-demand LLM execution architecture
  • Enforced end-to-end schema validation with Zod
  • Added rate limiting and centralized API error handling

Experience

Open Source Contributor

KanoDojo / Tadreeb LMS

  • Contributed features and fixes to production-grade open-source education platforms
  • Collaborated with maintainers through GitHub workflows and code reviews

Full Stack Developer Intern

CodeMyFYP

  • Built and maintained full-stack web application features
  • Worked across frontend, backend, APIs, and deployment workflows

Currently Exploring

  • Distributed Systems Fundamentals
  • System Design
  • Backend Scalability Patterns
  • Queue-Based Architectures
  • Cloud & Infrastructure Concepts

Connect

LinkedIn

LeetCode

Pinned Loading

  1. carvio carvio Public

    Pipeline-driven job & internship alert system that aggregates, filters, and delivers relevant opportunities.

  2. brevis brevis Public

    A minimalist, privacy-first platform for emotional expression and quiet release.

  3. ai-assisted-journal-system ai-assisted-journal-system Public

    Full-stack AI journal system demonstrating REST API design, LLM integration, and scalable backend architecture using Node.js, Express, TypeScript, MongoDB, and Next.js.

    TypeScript