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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM60034

AI-POWERED RESUME INTELLIGENCE SYSTEM USING LLM AND RETRIVAL AUGMENTED GENERATION

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM60034

Volume:

10 |

4 |

April 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

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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.

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Authors

K.

Kamalaveni .V

M.

Midunavarsini .B

S.

Sarayuma .M

SS

Shikha Srinivas

S.

Sooriya .G.M

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Abstract

The fast-changing nature of the labor market is driving the need to have intelligent systems that are able to effectively determine the skill profiles of individuals and match the ever-changing needs in the industry. The conventional Applicant Tracking Systems (ATS) are based on

KEYWORDS

based matching which frequently does not reflect the semantic associations between the skills acquired by candidates and the job description. The current paper presents a proposal for an Adaptive Career Intelligence Agent that combines Multi-Source Retrieval-Augmented Generation (RAG) with Explainable Artificial Intelligence (XAI) to provide context-relevant and trustworthy career data. It uses a dual-source retrieval system that processes user resumes and industry job descriptions in a FAISS-based vector database with HuggingFace semantic representations and similarity search. A big language model (Gemini 1.5 Flash) does structure skill classification classifying the skills into Core Competitive and Future. An explainability layer makes all outputs have a foundation on retrieved sources enhancing transparency and minimizing hallucinations. Also there is a career trajectory module that determines the skill gaps and suggests individual development routes. The proposed architecture is scalable cost-effective and applicable to the real-world implementation

Cite This Article

Kamalaveni .V, Midunavarsini .B, Sarayuma .M, Shikha Srinivas, Sooriya .G.M, "AI-POWERED RESUME INTELLIGENCE SYSTEM USING LLM AND RETRIVAL AUGMENTED GENERATION," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, April 2026.

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Publication Date

4/13/2026

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Double-Blind Peer Review

Review Rounds: 2

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