AI Resume Builder: A Locally Deployed Large Language Model Approach for Personalised Resume Generation

Abstract

This Paper introduces an AI-driven Resume Builder that utilises a hosted Large Language Model (LLM), DeepSeek-R1, to create context-sensitive, polished resumes through sophisticated prompt engineering. Unlike cloud-hosted solutions, this platform guarantees data privacy, faster resume generation, and offline operation. It combines a React frontend with a Spring Boot backend for data management and response generation. The proposed architecture automates the resume creation process by interpreting user-provided details and transforming them into industry-compliant, ATS-friendly formats. Evaluation results demonstrate that the system significantly improves personalisation, consistency, and privacy compared to existing online solutions. The findings highlight how local deployment of LLMs can redefine secure AI-driven automation for educational and recruitment purposes.