EMPLOYMENT HIRING PLATFORM USING AI

Abstract: This paper presents JobVista, a full stack employment hiring platform designed to support students, job seekers, and recruiters through a role-aware digital recruitment workflow. The platform provides secure authentication, candidate profile management, recruiter company management, job posting, job browsing, application tracking, applicant review, and assistant-driven guidance through JobMate. The implemented system uses React, Vite, Redux Toolkit, Express.js, Node.js, MongoDB, Mongoose, JWT-based cookie authentication, and bcrypt password hashing. JobVista also improves early platform usefulness by showing selected external opportunities and by providing template and Gemini-backed assistant responses for resumes, interviews, cover letters, job posts, and screening questions. The paper discusses the problem background, proposed methodology, architecture, database design, module implementation, testing, results, limitations, and future enhancements. The final system demonstrates that a college- level job portal can be technically meaningful, visually usable, and extensible without becoming unnecessarily complex.

Keywords: JobVista, job portal, employment hiring platform, React, Node.js, Express.js, MongoDB, role-based access control, application tracking, JobMate, AI career assistant