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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64705
Volume:
10 |
6 |
Jun 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Master of Computer Application
Nehru Institute of Information Technology and Management

Master of Computer Application
Nehru Institute of Information Technology and Management
Career planning and professional development have become increasingly challenging due to rapid technological advancements and evolving job market requirements. Students and job seekers often struggle to identify suitable career paths, prepare professional resumes, and develop interview skills. This paper presents an AI Career Coach, an intelligent web-based platform designed to assist users in career guidance, resume building, cover letter generation, and interview preparation. The system integrates Generative Artificial Intelligence to provide personalized recommendations based on user profiles, skills, interests, and career objectives. The platform is developed using Next.js for the frontend, Prisma ORM for database management, Clerk for authentication, and Google's Gemini AI model for intelligent content generation. The proposed system aims to reduce the gap between academic learning and industry requirements by offering automated and personalized career support. Experimental evaluation demonstrates that the platform improves resume quality, enhances interview readiness, and provides accurate career recommendations. The AI Career Coach serves as a scalable and efficient solution for students, graduates, and professionals seeking career development assistance.
KEYWORDS
This paper presented the design and implementation of an AI Career Coach, a web-based intelligent platform developed to support career development activities. The system integrates modern web technologies with Generative Artificial Intelligence to provide career recommendations, resume generation, cover letter creation, interview preparation, and performance analytics. The implementation results indicate that the platform effectively assists users in making informed career decisions while reducing the time and effort required for career planning. By providing personalized and scalable support, the system bridges the gap between academic learning and industry expectations. The proposed solution demonstrates the practical application of Artificial Intelligence in career guidance and professional development. The platform can serve as a valuable tool for students, graduates, and working professionals seeking career advancement opportunities.
[1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th Edition, Pearson, 2021. [2] T. Brown et al., “Language Models are Few-Shot Learners,” Advances in Neural Information Processing Systems, vol. 33, pp. 1877–1901, 2020. [3] Google DeepMind, "Gemini API Documentation," Google AI for Developers, 2025. Available: https://ai.google.dev [4] Vercel Inc., "Next.js Documentation," Next.js Official Documentation, Version 15, 2025. Available: https://nextjs.org/docs [5] Prisma Data Inc., "Prisma ORM Documentation," Prisma Official Documentation, 2025. Available: https://www.prisma.io/docs [6] Clerk Inc., "Clerk Authentication and User Management Documentation," Clerk Official Documentation, 2025. Available: https://clerk.com/docs [7] M. R. Islam and S. Rahman, “Artificial Intelligence in Career Recommendation Systems: A Survey,” International Journal of Computer Applications, vol. 184, no. 12, pp. 15–23, 2023. [8] A. Kumar and R. Sharma, “Intelligent Resume Recommendation and Screening Using Machine Learning,” Journal of Information Systems, vol. 11, no. 4, pp. 45–53, 2024. [9] J. Smith, “AI-Based Interview Assessment Systems and Their Applications,” International Journal of Advanced Computing Research, vol. 15, no. 2, pp. 100–108, 2024. [10] World Economic Forum, “Future of Jobs Report,” 2025.
Publication Date
6/9/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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