Smart Resume Builder: An Intelligent Full-Stack Web Application for Automated Professional Resume Generation Using Artificial Intelligence
DOI:
https://doi.org/10.64751/Abstract
In today's highly competitive job market, a well-structured and professionally formatted resume is one of the most critical tools for career success. However, a large proportion of job seekers — particularly students and fresh graduates — face significant challenges in creating effective resumes due to limited knowledge of professional formatting standards, document design, and industry-specific presentation requirements. Traditional manual resume creation using word processors such as Microsoft Word is time-consuming, technically demanding, and often produces inconsistent and poorly structured outputs. Existing online resume builder platforms, while helpful, suffer from critical limitations including restricted free access, limited template customization, complex user interfaces, absence of intelligent writing assistance, and inadequate optimization for Applicant Tracking Systems (ATS). This paper presents the Smart Resume Builder, a comprehensive, full-stack intelligent web application that automates and simplifies professional resume creation. The system is built upon a modern technology stack comprising React, Vite, Redux Toolkit, Tailwind CSS, and Radix UI for the frontend, with Node.js and Express.js powering the backend. MongoDB is used as the primary database through Mongoose ORM, and Clerk combined with JSON Web Tokens (JWT) manages secure user authentication and session management. A key innovation of the platform is the integration of Google Generative AI, which provides intelligent content suggestions including professional summaries, skill recommendations, and experience descriptions tailored to individual user profiles. The system provides a structured, form-based interface for entering all resume sections — personal details, educational background, technical skills, work experience, projects, and certifications — and automatically generates a well-formatted, ATS-optimized resume. Users can preview the formatted resume in real-time and download it as a professional PDF document. Functional testing across twelve test cases confirmed reliable performance across all modules. The system successfully addresses the major limitations of existing resume builders and provides a free, accessible, intelligent, and user-friendly solution for modern career development. Future enhancements include multiple template designs, cloud-based resume storage, job portal integration, AI-driven resume scoring, and interview preparation modules.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.







