In the modern job market, technological advancements have transformed the recruitment process, making it more data-driven and automated. Traditional resume-building methods often fail to highlight candidates' true potential due to generic formats, lack of personalization, and static content. To address these challenges, this paper presents a Smart Resume Builder, an AI-powered system that enhances career opportunities by leveraging machine learning (ML), natural language processing (NLP), and cloud computing. The proposed system dynamically generates resumes tailored to specific job roles by analyzing industry trends, job descriptions, and candidates' skills. This research explores the limitations of conventional resume-building tools and introduces a data-driven approach that integrates applicant tracking system (ATS) optimization, automated keyword enrichment, and personalized career recommendations. By employing NLP techniques, the system refines language, suggests impactful phrases, and ensures grammatical accuracy. Additionally, ML algorithms assess candidates’ skills, experience, and achievements to align them with industry demands, increasing the chances of selection. Furthermore, this study examines user experience (UX) factors, evaluating the effectiveness of interactive templates, customizable designs, and real-time feedback mechanisms. A cloud-based implementation ensures accessibility and seamless integration with professional networking platforms such as LinkedIn, enabling direct employer engagement. The paper also addresses ethical considerations, including data privacy, algorithmic bias, and transparency in AI-generated content. The research methodology involves a comparative analysis of traditional and smart resumes, performance evaluation using real-world recruitment datasets, and user feedback assessment. The results demonstrate that AI-powered resume builders significantly enhance candidates’ visibility, improve hiring efficiency, and reduce recruiter bias by presenting objective, data-backed profiles. The findings emphasize the potential of Smart Resume Builder systems to revolutionize job applications, bridging the gap between job seekers and employers. Future work includes expanding the system’s capabilities with deep learning models, multilingual support, and blockchain-based credential verification. This study contributes to the evolving domain of career technology,