International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 05 | May 2025
p-ISSN: 2395-0072
www.irjet.net
NEXTSTEP AI: All-in-One Hiring & Job Assistance Platform Angad Kumar1, Divyanshu Kumar2, Amanatullah3, Manoj Kumar Yadav4 1-4 Student Computer Science and Information Technology, Dronacharya Group of Institutions, U.P, India 5 Assist. Professor, Dept. of Computer Science and Information Technology, Dronacharya Group of Institutions, U.P,
India ---------------------------------------------------------------------***--------------------------------------------------------------------workflows and inconsistent evaluations. Static coding Abstract - The increasing complexity of remote technical
assessments fail to simulate real-world collaboration, and interviews conducted separately from coding tasks hinder a holistic view of candidate capabilities. Moreover, manual resume reviews are time-consuming, error-prone, and often biased due to subjective judgment or keyword dependency.
recruitment necessitates integrated solutions that address both assessment accuracy and hiring efficiency. NEXTSTEP AI – All-in-One Hiring & Job Assistance Platform is designed as a comprehensive, modular system that unifies collaborative coding environments, AI-driven interview analysis, automated resume screening, and secure video conferencing into a single intelligent hiring solution. This study presents the architecture, implementation, and performance evaluation of NEXTSTEP AI. The platform supports live coding using Socket.IO and Monaco Editor, WebRTC-based interview communication, resume parsing through TF-IDF and cosine similarity, and recruiter dashboards powered by AI analytics to ensure unbiased and data-driven decision-making. A simulated pilot deployment involving recruiters and software engineering candidates demonstrated notable improvements in candidate evaluation, recruiter efficiency, and overall user experience compared to traditional platforms. The results suggest that NEXTSTEP AI’s unified approach significantly enhances the fairness, speed, and effectiveness of remote hiring. Future work will focus on scalability to support enterprise-level loads, broader role inclusion beyond software development, and deeper AI integration to further personalize the recruitment experience.
To address these gaps, there is a growing demand for an integrated recruitment solution that combines real-time collaborative coding, AI-driven evaluation, resume automation, and secure video communication within a single platform. Such a system would enhance recruiter productivity, streamline the hiring process, and offer candidates a more engaging, realistic assessment experience. NEXTSTEP AI – All-in-One Hiring & Job Assistance Platform fulfils this need by offering a unified, scalable platform. It incorporates live coding using Monaco Editor and Socket.IO, AI-based candidate analysis, resume parsing via TF-IDF and cosine similarity, and WebRTCpowered video interviews. Recruiter dashboards provide actionable insights to support data-driven hiring decisions. This paper discusses the motivation, architecture, and implementation of NEXTSTEP AI, alongside its simulated evaluation, to demonstrate its impact on improving fairness, efficiency, and effectiveness in modern technical recruitment.
Key Words: AI-Powered Recruitment Platform, RealTime Code Collaboration, WebRTC Video Interviews, Automated Resume Parsing, Collaborative Coding Environment.
1.1 Objectives
1.INTRODUCTION
The primary objective of NEXTSTEP AI – All-in-One Hiring & Job Assistance Platform is to design a unified, intelligent recruitment platform that streamlines the technical hiring workflow by integrating collaborative coding tools, automated resume analysis, AI-powered evaluations, and secure video communication within a single, scalable system. By merging key recruitment functionalities into a modular architecture, NEXTSTEP AI eliminates the inefficiencies and subjectivity often associated with conventional hiring platforms. The platform is developed with a strong focus on automation, data security, and seamless candidate-recruiter interaction, aiming to deliver a faster, fairer, and more effective hiring experience.
The rapid evolution of remote work and global talent acquisition has significantly reshaped technical recruitment, driving the need for platforms that support real-time interaction, unbiased evaluation, and seamless user experience. Traditional job portals often rely on static assessments, manual resume screening, and fragmented tools, which limit their effectiveness in accurately identifying top technical talent—particularly in remotefirst environments. While several platforms offer solutions like resume filtering, coding tests, or video interviews, they function in isolation. This fragmentation results in inefficient
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