AI Resume Builder: An Intelligent Framework for ATS Optimization and SkillBased Job Matching
Keywords:
Artificial Intelligence, Resume Builder, Natural Language Processing (NLP), Large Language Models (LLMs), Applicant Tracking Systems (ATS), Retrieval-Augmented Generation (RAG), Semantic Similarity, Resume Optimization, Skill Gap Analysis, Transformer Models, Job-Resume Matching, Algorithmic Fairness, AI-Based Recruitment, Automated Resume Generation, Ethical AI.Abstract
In the contemporary job market, the increasing volume of applications has led to the widespread adoption of Applicant Tracking Systems (ATS) by recruiters. However, job seekers often face challenges in optimising their resumes to meet these algorithmic criteria. This paper presents the design and implementation of an AI-powered Resume Builder, a comprehensive web-based platform that leverages Natural Language Processing (NLP) and Large Language Models (LLMs) to automate resume generation and refinement. The proposed system integrates advanced techniques such as Retrieval Augmented Generation (RAG), semantic similarity analysis, and transformer-based parsing to provide personalised content suggestions, ATS scoring, and skill-gap analysis. Empirical evidence suggests that AI-driven optimisation can reduce processing time by up to 95% and significantly improve candidate-job alignment. This study further explores the ethical implications of algorithmic hiring, addressing biases in LLM-based screening and proposing mitigation strategies for equitable recruitment.
Index Terms—AI resume builder, natural language processing, large language models, applicant tracking systems, semantic matching, resume optimisation, algorithmic fairness.
References
Chafiq N, El Ghazouani M, El Gounidi R. From manual review to AI automation: An NLP-powered system for efficient CV processing in academic admissions. LatIA. 2025(3):315..
Swetha G, Shruthi KN, Sushma R, Kruthi TC, Veena MS, Tejaswini K. AI-Powered Smart Resume Analyzer: An NLP and Deep Learning-Based Framework for Automated Candidate Profiling and Recruitment Optimization. In2025 IEEE 4th International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET) 2025 Oct 8 (pp. 1-6). IEEE.
M. Mohanan, P. Belwal, S. Kapoor, S. Sharma, and Mrs. K. Kushwah, "Revolutionizing Career Advancement: A Comprehensive Research on a Resume Builder Application," International Journal for Research in Applied Science and Engineering Technology, 2024.
Zinjad SB, Bhattacharjee A, Bhilegaonkar A, Liu H. Resumeflow: An llm-facilitated pipeline for personalized resume generation and refinement. InProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval 2024 Jul 10 (pp. 2781-2785).
Dr. CH R. Babu, "RESUMATE: A Smart Resume Builder Using AI for Personalized Content and Professional Profile Management," 2025.
Kumar G, Kumar D, Behera P. Analyzing Resume with AI–Get Hired. International Journal of Data Science. 2025 Jun 27;6(1):1-0.
Deshmukh S, Bajaj A. CareerBoost: A hybrid RAG-NLP job recommendation framework. In2024 8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC) 2024 Oct 3 (pp. 853-858). IEEE.
Veldanda AK, Grob F, Thakur S, Pearce H, Tan B, Karri R, Garg S. Are Emily and Greg still more employable than Lakisha and Jamal? Investigating algorithmic hiring bias in the era of ChatGPT. arXiv preprint arXiv:2310.05135. 2023 Oct 8.
Bharathesh K, S. Shetty, N. M. Shetty, P. V. Naik, and H. Triloknath, "AI-Driven Resume Analysis and Optimization System for Enhanced Job Market Compatibility," Sparklinglight Transactions on Artificial Intelligence and Quantum Computing (STAIQC).
Rao DS, Meharunnisa S, Nikhilesh C, Abhisreshta B. AI-Powered Multi-Language Resume Analyzer And Job Recommendation System. In2026 9th International Conference on Circuit, Power & Computing Technologies (ICCPCT) 2026 Aug 6 (pp. 253-260). IEEE.
T - Manojpraphakar, A. K. S, A S - Bhavatarini, C S - Darsini, and D. B., "Hiresense: ai-driven talent matcher," International Journal For Multidisciplinary Research, 2025.
Swetha G, Shruthi KN, Sushma R, Kruthi TC, Veena MS, Tejaswini K. AI-Powered Smart Resume Analyzer: An NLP and Deep Learning-Based Framework for Automated Candidate Profiling and Recruitment Optimization. In2025 IEEE 4th International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET) 2025 Oct 8 (pp. 1-6). IEEE.
Butwall M, Kumar S, Bhojwani G, Yashkumar H, Boolchandani K. MODEX: A Web-Based Resume Generation System Powered by Transformer Models and Adaptive Template Rendering.
Xu J, Li G, Jiang JY. AI self-preferencing in algorithmic hiring: Empirical evidence and insights. arXiv preprint arXiv:2509.00462. 2025 Aug 30.
Balaji J. Airesume: Automated generation of resume work history.
Dr. C. S. Pillai, C. R. Ankitha, H. C. R, and K. Malviya, "AI-Powered Automated Resume Screening System," International Journal Of Scientific Research In Engineering & Technology, 2026.
Shareef DK, Sulthana AS, Rajeswari J, Vasavi G, Vasavi G. A Unified AI-Powered Resume Generation and ML-Based Candidate Filtering Framework for Smart Campus Recruitment. In2026 7th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI) 2026 Jan 7 (pp. 1085-1092). IEEE..
