Automated Resume Formation Using Generative Artificial Intelligence

Abstract

The article examines the development process of an intelligent system for automated resume generation based on generative artificial intelligence and modern web technologies. The study's relevance is driven by the growing need for fast, high-quality creation of professional resumes tailored to specific job requirements and to applicant tracking systems (ATS). The aim of this work is to develop a software module that enables users to generate a structured resume from a brief textual description of their experience, skills, and professional achievements. The study analyzes existing resume-building services, identifies their advantages and disadvantages, and formulates both functional and non-functional system requirements. The software product is implemented using TypeScript, the NestJS and Next.js frameworks, PostgreSQL, and Prisma ORM. Text generation is performed using the OpenAI API, while document generation in PDF format is implemented using PDFKit. The proposed system provides content personalization, multilingual support, document history storage, and resume export. Testing results confirm the module's stable performance, high-quality generated text, and a significant reduction in document preparation time. The developed solution can be used as a standalone web service or integrated into HR platforms and electronic employment systems.