This study addresses the challenge of limited employment accessibility in rural communities through the development of a Web - Based Localized Job - Finding System I. INTRODUCTION designed for Dumangas, Iloilo. While existing online job portals predominantly prioritize urban labor markets, the Digital employment platforms have transformed proposed system establishes a dedicated digital infrastructure recruitment processes globally; however, their focus that connects local job seekers with nearby employment opportunities and supports employers through centralized remains predominantly urban - centric. Rural municipalities recruitment tools. The system was developed using the Agile such as Dumangas, Iloilo experience limited access to Sc rum methodology to enable iterative development and structured digital employment infrastructures . Job seekers continuous stakeholder feedback. It integrates an Artificial rely heavily on informal recruitment methods, including Intelligence – based job - matching mechanism utilizing Natural word - of - mouth and social media postings, resulting in Language Processing (NLP) techniques to analyze job seeker inefficiencies and reduced employment transparency. profiles and job posting s and generate personalized Existing job portals such as JobStreet and LinkedIn employment recommendations. Core system features include provide large - scale recruitment ecosystems but lack secure user authentication, job posting and application localization mechanisms tailored to specific municipalities. management, application tracking dashboards, integrated messaging, real - time notifications, and a rating and feedba ck This creates a structural accessibility gap for rural labor system. System evaluation was conducted using the ISO/IEC markets. 25010 software quality model, with assessments provided by This study proposes a Web - Based Localized Job - domain users and IT experts across key quality characteristics. Finding System specifically designed for Dumangas. Unlike Evaluation results indicate that the system met the established general - purpose portals, the system restricts job listings to software quality standards and was perceived as effective and verified local employers and integrates AI - driven job user - friendly. The findings demonstrate that the proposed matching optimized for small - scale l abor markets. system can significantly enhance local employment The primary contribution of this study lies in the accessibility, reduce reliance on informal recruitment methods, integration of localized filtering mechanisms with AI - based and serve as a viable model fo r localized digital employment platforms in rural municipalities. semantic matching while maintaining compliance with ISO/IEC 25010 software quality standards [3] .