Smart Job Portals: The Intersection of AI and Recruitment Efficiency

Abstract Job portals from the past decade encounter major performance limitations when they process large candidate applications alongside effective job opportunity assignment for suitable candidates. The paper describes how a Smart Job Portal employs Artificial Intelligence technology to enhance recruitment performance and decrease human errors during job acquisition. Users of this system gain advantage from automated resume screening services and AI-generated recommendation systems that display application progress updates and deliver analytical insights on an analysis dashboard through data analytical tools combined with machine learning technology and automation. The internet portal implements a framework that uses React and Node.js technologies as well as TensorFlow.js and NLTK machine learning frameworks to deliver responsive scalable ethical capabilities. This paper analyzes system technical infrastructure through detailed explanations of how datasets are prepared and how models are tested for practical applications which demonstrate how the system can transform recruitment while enhancing candidate interfaces. Keywords: The terms ethical AI, automation, job matching, machine learning and resume screening, smart job portal alongside application tracking, applicant experience, and recruitment efficiency come into play.