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Full Stack Engineer with less than a year in MERN Stack & AI Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated Full Stack Engineer with 9 months of internship experience in MERN stack and backend development. Proven ability to contribute to live mobile applications, develop robust backend services with Node.js and Express.js, and manage application data with MongoDB. Skilled in building real-time, AI-powered platforms and e-pharmacy solutions using React, TypeScript, and various modern web technologies.
Institute of Hotel & Restaurant Management
Bachelor of Computer Application
August 1, 2022 – June 30, 2025
Mahendranath-High School
XII
June 1, 2021 – May 31, 2022
Zenithyuga
MERN Web Developer Intern
October 1, 2025 – December 1, 2025
India
Aham Innovations
Backend Developer Intern
February 1, 2025 – April 1, 2025
Kolkata, West Bengal, India
Interview AI
December 1, 2025 – January 1, 2026
Built Interview-AI, a real-time AI-powered technical interview platform using React 19 (TypeScript, Tailwind CSS v4, Radix UI) and Node.js with Express 5, integrating MongoDB (Mongoose), Socket.io, JWT authentication, and OpenAI SDK (Perplexity Sonar models) to deliver a scalable, modern full-stack application. Developed a context-aware interview engine that generates dynamic questions based on role, topic, and parsed resume data; implemented real-time WebSocket-driven interview flow, AI-based answer evaluation (correctness, depth, clarity), smart LLM response caching to reduce cost and latency, and automated post-interview reports with hiring recommendations.
Pharmanest
September 1, 2025 – November 1, 2025
Developed PharmaNest, a full-stack E-Pharmacy & Telemedicine platform using React 19 (TypeScript, TailwindCSS 4, Framer Motion) and Node.js with Express & MongoDB, integrating JWT authentication, Cloudinary storage, Razorpay payments, and Socket.io for real-time communication in a secure, production-ready architecture. Engineered a custom WebRTC-based telemedicine system (peer-to-peer video/voice via Socket.io signaling) and implemented a context-aware AI Health Advisor using a RAG pipeline (MongoDB text search + LLM integration), along with automated inventory monitoring using cron jobs and Mongoose middleware for data integrity and cascading operations.
Cultural Fit Analysis
The candidate's personal projects demonstrate a strong drive for learning and applying cutting-edge technologies (WebRTC, RAG, LLMs). The diversity of projects (e-pharmacy, AI interview platform) indicates a broad interest in different application domains. While the experience is primarily in personal projects and internships, the ambition and technical depth shown align well with a culture that values innovation and continuous learning. However, the lack of extensive professional experience might require mentorship to fully integrate into a senior team's operational rhythm.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and innovative approach to problem-solving, particularly in developing complex, real-time systems. The experience in collaborative development teams during internships suggests an ability to work effectively with others. The detailed project descriptions also show good technical communication skills in explaining complex architectures and features.