Rahul Tapase is a full-stack developer based in Navi Mumbai, Maharashtra, India. He specializes in LLM-integrated applications and scalable backend systems, building production-ready software across authentication, real-time features, and AI-augmented workflows.
As a full-stack developer, Rahul Tapase is proficient in:
Rahul Tapase is a B.Tech Computer Science & Engineering student at IIIT Pune (Nov 2022 – May 2026).
Looking to connect with a full-stack developer? Reach Rahul Tapase at hello@rahultapase.dev. Rahul Tapase is open to internship, full-time, and remote opportunities.
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Rahul Tapase - Full-Stack Developer | Next.js, React, TypeScript, Node.js
CRAFTING LLM-INTEGRATED APPS &
SCALABLE BACKENDS
My toolkit
Case studies
Multi-Model AI Consensus Platform
A 3-stage AI consensus pipeline where up to 5 LLMs answer a query in parallel, anonymously rank each other's responses, and synthesize a single high-quality final answer.
AI-Powered Mock Interview Platform
An AI mock-interview platform that simulates realistic technical and behavioral interviews tailored to a user's role, industry, and experience level.
Know about me
Full-stack developer focused on LLM-integrated apps and scalable backends with Next.js, React, TypeScript, and Node.js. I focus on clean architecture, real-time features, and AI-augmented workflows — and I care about building things that actually work in production.
Based in IST (UTC+5:30) and comfortable collaborating with global, remote teams.
Explore my site
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From the desk
I'm setting up a place to write about building LLM-integrated apps, scalable backends, and the things I learn along the way. Check back soon.
Visit the blogI'm available for internship, full-time, and remote opportunities. If you're building something ambitious, I'd love to hear about it.
Get to Know Me
Developer by day, problem solver by nature. Let's build something amazing together.
Rahul Tapase is a full-stack developer based in Navi Mumbai, Maharashtra, India, specializing in LLM-integrated applications and scalable backend systems with Next.js, React, TypeScript, and Node.js. Rahul builds production-ready software like LLM Consensus, PrepMate, Zorvyn Finance, and RideSync, covering authentication, real-time features, and AI-augmented workflows.
Notable projects by Rahul Tapase include LLM Consensus (a multi-model AI consensus platform), PrepMate (an AI mock interview platform), Zorvyn Finance (a role-based finance dashboard API), and RideSync (a real-time ride-sharing app).
Rahul Tapase is a B.Tech Computer Science & Engineering student at IIIT Pune (Nov 2022 – May 2026).
Location: Navi Mumbai, Maharashtra, India
Email: hello@rahultapase.dev
Rahul Tapase is open to internship, full-time, and remote opportunities worldwide
Projects Built
Years Coding
Technologies
Rahul Tapase builds production-ready full-stack systems with clean architecture and thoughtful user experiences.
Specializing in LLM-integrated applications and scalable backends — across auth, real-time features, and AI-augmented workflows.
Thank you for being part of my journey
Ready to bring your vision to life?
What I Do
End-to-End Solutions
Building complete web applications from database to pixel-perfect UI. I ship production-ready full-stack products with clean, maintainable architecture using Next.js, React, and Node.js.
Tech Stack
Key Highlights
Interested in this service?
Let's discuss your project
The Story So Far
Began my Computer Science & Engineering journey at IIIT Pune, diving into data structures, algorithms, and web development fundamentals.
Began my Computer Science & Engineering journey at IIIT Pune, diving into data structures, algorithms, and web development fundamentals.
Built RideSync, a real-time ride-sharing platform with Mapbox and Stripe, and Zorvyn Finance, a role-based finance dashboard API with NestJS and Prisma.
Built RideSync, a real-time ride-sharing platform with Mapbox and Stripe, and Zorvyn Finance, a role-based finance dashboard API with NestJS and Prisma.
Built PrepMate (AI mock interviews with Gemini) and LLM Consensus, a multi-model AI consensus platform with real-time streaming and RAG-style workflows.
Built PrepMate (AI mock interviews with Gemini) and LLM Consensus, a multi-model AI consensus platform with real-time streaming and RAG-style workflows.
Graduating in May 2026 and focused on building LLM-integrated applications and scalable backend systems. Open to internship, full-time, and remote opportunities.
Graduating in May 2026 and focused on building LLM-integrated applications and scalable backend systems. Open to internship, full-time, and remote opportunities.
Rahul Tapase works across the full stack with a focus on LLM-integrated applications and scalable backend systems, spanning frontend, backend, databases, AI/LLM tooling, and DevOps.
My Arsenal
Building modern web experiences with cutting-edge tools and frameworks
Explore a curated collection of production-ready applications built by Rahul Tapase, highlighting full-stack engineering, LLM integration, and scalable backend development.
Multi-Model AI Consensus Platform - A 3-stage AI consensus pipeline where up to 5 LLMs answer a query in parallel, anonymously rank each other's responses, and synthesize a single high-quality final answer.
Technologies: Next.js, FastAPI, TypeScript, Supabase, Drizzle ORM, Redis
AI-Powered Mock Interview Platform - An AI mock-interview platform that simulates realistic technical and behavioral interviews tailored to a user's role, industry, and experience level.
Technologies: React.js, TypeScript, Tailwind CSS, Firebase, Google Gemini, Vite
Role-Based Finance Dashboard API - A modular finance backend API built with NestJS and Prisma, featuring role-based access control for Admin, Analyst, and Viewer workflows.
Technologies: NestJS, TypeScript, Prisma, PostgreSQL, Swagger, Neon
City-Wide Ride Sharing App - A full-stack ride-sharing platform built with Next.js and the Mapbox API, featuring real-time location tracking and route visualization.
Technologies: Next.js, React.js, TypeScript, Tailwind CSS, Stripe, Socket.io, Mapbox
Portfolio
A curated collection of full-stack applications showcasing modern web technologies and innovative solutions.
Multi-Model AI Consensus Platform
A 3-stage AI consensus pipeline where up to 5 LLMs answer a query in parallel, anonymously rank each other's responses, and synthesize a single high-quality final answer.
Real-time, stage-wise response streaming via Server-Sent Events
Supabase authentication with conversation history and CRUD
Redis rate limiting, markdown/code/diagram rendering, and voice input
AI-Powered Mock Interview Platform
An AI mock-interview platform that simulates realistic technical and behavioral interviews tailored to a user's role, industry, and experience level.
Gemini-generated adaptive questions with instant contextual feedback
Firebase auth with email and Google OAuth login
Session analytics with performance tracking and progress dashboards
Role-Based Finance Dashboard API
A modular finance backend API built with NestJS and Prisma, featuring role-based access control for Admin, Analyst, and Viewer workflows.
18 documented REST endpoints for auth, users, records, and analytics
JWT authentication, DTO validation, and soft-delete patterns
Interactive Swagger + Scalar API docs deployed on Render
Click to reveal more innovative projects
Rahul Tapase is open to internship, full-time, and remote opportunities, as well as collaboration on full-stack and LLM-integrated projects. He builds scalable web applications and backend systems with Next.js, React, TypeScript, Node.js, NestJS, and FastAPI.
Name: Rahul Tapase
Title: Full-Stack Developer
Email: hello@rahultapase.dev
Location: Navi Mumbai, Maharashtra, India
Website: https://rahultapase.dev
Rahul is open to internship, full-time, and remote opportunities, and is flexible across time zones. Best way to reach him is by email at hello@rahultapase.dev or via LinkedIn.
Whether it's an LLM-integrated product or a scalable backend, I'd love to help bring your idea to life.
Open to internship, full-time, and remote opportunities.
I focus on shipping clean, scalable systems that support real users and growing products.
