Abstract: Conventional job portals often struggle with irrel- evant recommendations, poor user engagement, and inefficient recruiter workflows. This research introduces a uniquely struc- tured Online Job Portal that leverages real-time matching algo- rithms, context-aware filtering, and a modular service-oriented backend. Unlike existing systems, our platform emphasizes role- personalized user journeys, resume intent extraction, and scalable design for academic and SME integration. The architecture sup- ports dynamic content rendering and automated feedback loops, significantly reducing manual intervention. Results demonstrate improved candidate relevance and reduced recruiter screening time, positioning the system as a viable next-gen recruitment solution.

Index Terms: Online Job Portal, Digital Recruitment, Intelli- gent Filtering, Resume Matching, Scalable Architecture

| DOI: 10.17148/IARJSET.2025.12705