The swift progression of technology and the widespread availability of the Internet have profoundly altered how job seekers obtain and employ information. This article outlines the creation of an online job search engine aimed at rectifying inefficiencies in the existing job search process. The proposed metasearch engine utilizes advanced technologies, including microservices architecture, Docker containerization, and asynchronous programming with the Aiohttp library, to gather job offers from several sources and display them user-friendly. This method decreases operational expenses and mitigates extraneous information. Essential system components comprise Docker for service orchestration, RabbitMQ for effective inter-microservice communication, and a user-focused interface for the filtration of job listings by technology, location, or income. The system's architecture guarantees scalability, maintainability, and enhanced performance, rendering it an invaluable resource for job seekers. Our research underscores the significance of strategic job searching through social media, networking, and meticulously designed resumes. The results offer significant insights into employment-seeking behavior and the efficacy of various job search sites. Future endeavors will concentrate on incorporating supplementary data sources and deploying sophisticated search algorithms to improve the user experience further.