Artificial Intelligence-driven Enterprise Human Resource Recruitment Optimisation System Design

Abstract

This paper designs and implements an enterprise recruitment optimisation system based on artificial intelligence, using microservice architecture and deep learning technology. The system improves recruitment efficiency and quality through intelligent resume parsing, accurate job matching and automated assessment. Experimental results show that compared with the traditional way, the recruitment cycle is shortened by 44.0%, the per capita cost is reduced by 42.4%, and employee performance is improved by 20.8%. The system runs stably in a high concurrency environment, with a user satisfaction score of 4.6 (out of 5), providing effective technical support for enterprise talent acquisition.