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@article{203790,
        author = {Vikas D. Chavan and Shivaprasad S. Kumbhar and Mayur S. Jagadale and Nikhil G. Jadhav and Omkar V. Sabale},
        title = {AI Job & Skills Recommendation System Using CrewAI},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {319-322},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203790},
        abstract = {In today’s rapidly evolving technological world, students and job seekers often face challenges in selecting the right career path and identifying the skills required to remain competitive in the job market. Traditional job portals mainly focus on job listings and fail to provide personalized guidance, skill-gap analysis, and future career recommendations. To overcome these limitations, this research proposes an AI-Based Job and Skill Recommendation System using CrewAI, a multi-agent artificial intelligence framework that enables collaborative decision-making among intelligent agents.
The proposed system analyzes user profiles, educational background, interests, technical skills, certifications, and current market trends to provide accurate and personalized job recommendations. Multiple AI agents work together to perform specialized tasks such as profile analysis, skill matching, market trend analysis, career prediction, and roadmap generation. The system also identifies missing skills required for selected job roles and generates a structured learning roadmap to improve employability.},
        keywords = {CrewAI Multi-Agent System •	AI Job Recommendation •	Artificial Intelligence •	Career Recommendation System •	Learning Roadmap Generation •	Skill Gap Analysis •	Personalized Career Guidance},
        month = {June},
        }