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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67390
Volume:
10 |
9 |
Sep 2026
Pages:
1-6
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.
Department of Computer Science and Engineering
P R Pote Patil College Of Engineering and Management, Amravati
Department of Computer Science and Engineering
P R Pote Patil College Of Engineering and Management, Amravati
Department of Computer Science and Engineering
P R Pote Patil College Of Engineering and Management, Amravati
Department of Computer Science and Engineering
P R Pote Patil College Of Engineering and Management, Amravati
Department of Computer Science and Engineering
P R Pote Patil College Of Engineering and Management,, Amravati
Department of Computer Science and Engineering
P R Pote Patil College Of Engineering and Management, Amravati
Recruitment has changed considerably as Artificial Intelligence (AI), Natural Language Processing (NLP), Generative AI, and cloud technologies have matured. Conventional hiring platforms mostly rely on keyword matching and manual screening of applicants, an approach that often yields irrelevant suggestions, misses candidates who are a good fit in substance but not in wording, and adds to a recruiter's workload. Applicants, too, are often left with little insight into their own skills, employability, or how to grow their careers. This review looks at intelligent hiring systems, with attention to AI-driven resume evaluation, semantic matching between candidates and roles, job recommendation, identification of skill gaps, automated screening, and career advice. It compares approaches built on keyword search, machine learning, NLP, Named Entity Recognition (NER), Transformer architectures, and Large Language Models (LLMs). Drawing on the gaps identified, the paper puts forward a methodology for Next Gen Hiring, an AI-powered job portal. The platform brings together Job Seeker, Employer, and Admin portals on top of Google Gemini AI and a cloud-native microservices stack built with Java, Spring Boot 4, Spring Cloud Gateway, Eureka, Kafka, Redis, PostgreSQL, React 19, and JWT-based security.
KEYWORDS
Artificial Intelligence is reshaping recruitment, moving it away from keyword-based filtering and toward evaluation that accounts for context. The approaches reviewed here show progress across resume parsing, NLP, machine learning, semantic matching, Transformer models, and Large Language Models. Even so, many of these systems handle only one part of the recruitment process and offer little connection between employer-side recruitment and candidate-side career development. Next Gen Hiring aims to close these gaps by proposing a connected ecosystem for job seekers, employers, and administrators. The platform pairs Google Gemini AI with Java Spring Boot 4 microservices to provide resume analysis, semantic job recommendations, candidate screening, skill-gap analysis, job-readiness assessment, career guidance, and AI-generated recruitment content, supported by React 19, Spring Cloud Gateway, Eureka, PostgreSQL, Redis, Kafka, Spring Security, and JWT. In short, the proposed system is intended to shift recruitment away from static keyword matching and toward an intelligent, semantic, skill-aware process, while giving job seekers career support they can actually act on.
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Publication Date
9/21/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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