CVForge: uma aplicação para criação de currículos personalizados com inteligência artificial

Abstract

This work presents the development of a web application capable of generating personalized résumés using Large Language Models (LLMs). The proposal arose from the increasing need for candidates to adapt their résumés to the specific requirements of each job opening, also considering the role of Applicant Tracking Systems (ATS) in modern recruitment processes. The theoretical foundation addresses concepts of artificial intelligence, machine learning, natural language processing, and recent studies on résumé personalization. The adopted methodology includes literature review, definition of the technologies used, system architecture design, and evaluation of the generated results. The application was developed using Next.js with direct integration to the OpenAI API, eliminating the need for a dedicated backend. The results demonstrate that the system can generate coherent, well-structured résumés tailored to the job description provided, evidence of the effectiveness of LLMs for this purpose. It is concluded that the tool facilitates the creation of professional résumés and can assist candidates in increasing their chances in contemporary selection processes. Future work may include the addition of new features such as cover letter generation and more detailed compatibility analysis between résumé and job requirements.