Job Search Agent Based System
Job Search Agent Based System
Authors:
1 M.Bharath Kumar, 2 Ch.Revanth, 3 N.Saikumar Goud, 4 T.Akshay
1,2,3,4 Students, Department of Computer Science & Engineering (Artificial Intelligence & Machine Learning),
Malla Reddy University, Kompally, Hyderabad.1 Email:2211CS020659@mallareddyuniversity.ac.in, 2 Email:
2211CS020663@mallareddyuniversity.ac.in, 3 Email: 2211CS020673@mallareddyuniversity.ac.in, 4
Email: 2211CS020691@mallareddyuniversity.ac.in
ABSTRACT
The rapid expansion of online recruitment platforms has significantly increased employment accessibility by providing job seekers with a vast number of opportunities across multiple industries. However, the large volume of job postings available on different platforms often makes it difficult for candidates to efficiently identify positions that match their skills, qualifications, and career interests. Job seekers are typically required to manually browse and filter numerous job listings while also managing applications across multiple websites. This process can be time-consuming, inefficient, and difficult to track effectively.
To address these challenges, this paper presents the design and implementation of a Job Search Agent Based System, an intelligent platform that automates resume analysis, skill extraction, and personalized job recommendation. The proposed system utilizes Natural Language Processing techniques to analyze unstructured resume documents and extract relevant information such as technical skills, educational background, and professional experience. The extracted information is then compared with job descriptions using similarity-based matching techniques to evaluate the compatibility between candidate profiles and job requirements.
Based on this comparison, the system generates a dynamic match score that ranks job listings according to their relevance to the candidate’s profile. This enables job seekers to quickly identify suitable opportunities without manually reviewing large volumes of job postings. The system architecture integrates a responsive web-based frontend, a FastAPI-based backend, and a structured SQL database for efficient data processing, storage, and application tracking. The platform also provides centralized management of job applications, allowing users to monitor the status of applied positions and maintain organized records.
Keywords— Artificial Intelligence, Resume Parsing, NLP, Recommendation System, Skill Matching, FastAPI.