Students preparing for technology-sector recruitment must manage resume preparation, job-description matching, vacancy discovery, interview practice, and industry updates. These activities are often spread over different platforms. This paper presents Skill2Hire, a modular AI-powered career assistance platform with five independent modules: an ATS-oriented Resume Builder, Resume Tailoring and Skill-Gap Analysis, Job Suggestions, a Mock Interview Simulator, and a Tech News Hub. The proposed system uses a React and TypeScript frontend, a Node.js and Express backend, MongoDB Atlas for persistent storage, and server-side large language model integration for selected language tasks. A rule-based ATS compatibility score estimates resume completeness, keyword alignment, skills coverage, structure, and formatting. Resume tailoring follows a “Zero Fake Skills” rule: missing qualifications are reported as skill gaps rather than inserted into the candidate’s resume. The interview module includes eligibility screening, aptitude assessment, technical interview, and behavioral HR stages.

The paper describes the design, workflows, architecture, responsible-AI safeguards, and evaluation plan. Claims of quantitative performance are not treated as findings unless measurements can be reproduced.

Keywords— Career assistance, Applicant Tracking System, resume tailoring, job recommendation, large language models, mock interview, skill-gap analysis.