Gen AI Job Preparation Web Application: An Intelligent Full-Stack Platform for Personalized Career Readiness and AI-Driven Interview Preparation

Abstract

The rapid advancement of digital technologies has significantly transformed the education and career development sectors by increasing the demand for intelligent, scalable, and user-friendly platforms. Traditional job preparation methods and existing online platforms often operate independently, suffering from fragmentation, generic content, and a lack of real-time personalized feedback. This research presents the comprehensive design, development, and implementation of the Gen AI Job Preparation Web Application, an AI-integrated full-stack platform that bridges this gap by providing a unified ecosystem for AI-powered mock interviews, resume analysis, skill assessments, and performance tracking. Engineered using modern frontend technologies including React.js, TypeScript, and Tailwind CSS, alongside a resilient backend powered by Node.js, Express.js, and MongoDB, the system establishes a centralized digital career preparation environment. Key functionalities include OTP-based secure user authentication governed by JSON Web Tokens (JWT), intelligent resume evaluation through the Gemini AI API, adaptive aptitude and technical assessments, and granular performance analytics. Experimental analysis demonstrates significant improvements in personalized interview preparation and user engagement, with stable performance across all implemented modules. The platform successfully resolves the fragmentation of existing systems, providing a secure, intelligent, and multifunctional environment suitable for students, fresh graduates, and professionals seeking career advancement.