Career Link: AI for Resumes, Interviews, and Career Advice

Abstract

Career Link is an AI-powered career guidance platform that integrates multiple intelligent tools to assist users in every step of their professional journey. The application offers an AI advisor for personalized career insights, an AI-powered resume builder, a roadmap generator, and a mock interview simulator, providing a holistic user experience. Career Link’s architecture leverages advanced language models such as Mistral and Google’s Gemini to deliver context-aware career recommendations, generate resume content, and simulate real-world interview scenarios. The system collects user inputs from psychometric personality tests, educational background, and professional interests, then applies clustering techniques and prompt engineering to generate detailed, tailored guidance. A case study involving a final-year student demonstrates how Career Link generates a career fit report, an optimized resume, and adaptive interview questions, significantly improving the user’s preparedness and self-awareness. This paper outlines the system\'s design, AI integration, and the real-world impact of combining psychometrics with large language models for scalable, personalized career guidance.

Introduction

Overview:
Career Link is an intelligent, modular career guidance platform designed to support students and early-career professionals through personalized, AI-driven advice. It overcomes limitations of traditional counseling by offering accessible tools powered by Mistral and Google Gemini large language models (LLMs). The platform includes four main modules:

• AI Career Advisor

• Resume Builder

• Interview Simulator

• Roadmap Explorer

System Architecture & Methodology:

Career Link is structured in three layers:

1. User Input Layer – gathers user data (skills, goals, experience).

2. AI Processing Layer – uses LLMs to generate personalized responses.

3. Storage Layer – MongoDB stores user data and interactions securely.

Each AI module is triggered based on the user’s selected activity. Mistral handles career advice, while Gemini powers resume generation and mock interviews. Static roadmaps are also available for self-guided exploration.

Modules & Personalization:

• Career Advisor (Mistral): Provides tailored career suggestions, skill gap analysis, and roadmaps based on user input.

• Interview Bot (Gemini): Simulates interviews using adaptive, real-time questioning with planned feedback integration.

• Resume Builder (Gemini): Generates ATS-optimized, action-oriented bullet points aligned with job goals.

• Roadmap Explorer: Offers curated, domain-specific study paths (non-AI).

Personalization is achieved through prompt engineering and context-aware inputs, ensuring advice is relevant to the user's role, experience, and goals.

Prompt Strategy & Model Behavior:

Prompt engineering defines each model’s tone, behavior, and constraints.

• Mistral’s tone is casual, supportive, and practical, acting like a mentor.

• Gemini’s mock interview prompts use structured templates to ensure realism and coherent follow-up questions.

Example Use Case:

A 19-year-old CSE student and part-time freelancer uses Career Link to:

• Get career advice: AI suggests focusing on Backend Development based on skills in Python and SQL.

• Build a resume: Gemini outputs impactful bullets, e.g., “Improved system performance by 15%.”

• Simulate interviews: Gemini asks relevant questions, gives constructive feedback, and adapts follow-up questions accordingly.

Key Strengths:

• Personalized, real-time guidance

• Integration of advanced LLMs

• Modular architecture supporting different user needs

• Clear prompt strategies for tone and content control

Conclusion

In this paper, we introduced Career Link, an AI-powered career guidance platform designed to support students and early professionals in navigating the complex world of career planning. By leveraging advanced large language models—Mistral for real-time advisory and Gemini for structured content generation—Career Link provides personalized support across key domains: career planning, resume development, and interview readiness. The system showcases the power of AI to deliver actionable insights tailored to a user\'s profile, while maintaining a tone that is both supportive and motivational. The case study of a CSE student with limited industry experience demonstrated Career Link’s effectiveness in mapping user skills to suitable career paths, optimizing resume content for internships, and simulating real-world interview interactions. The AI provided domain-relevant recommendations, generated professional resume outputs, and engaged the user in dynamic mock interviews with personalized feedback. These results underscore Career Link’s potential as a virtual career mentor—delivering high-quality, scalable, and affordable guidance traditionally reserved for one-on-one human counseling. Career Link’s approach—centered on prompt engineering, modular AI engines, and structured personalization—highlights the feasibility of combining psychometrics with generative AI for impactful decision support. It avoids complex pre-processing pipelines in favor of lightweight, context-aware prompting, offering a flexible foundation for future development. Looking ahead, several enhancements are possible. Future work may include real-time integration with professional platforms like LinkedIn or GitHub to autofill user data, the addition of AI-generated feedback summaries post-interview, and broader testing across user demographics to evaluate longitudinal impact on career success. Equally important will be ensuring ethical AI use, data privacy, and transparency as the system scales. In conclusion, Career Link represents a significant step toward democratizing personalized career development. By marrying state-of-the-art generative AI with pragmatic career-building strategies, it empowers users to navigate their professional journey with greater clarity, confidence, and preparedness. The promising results from our initial deployment suggest that AI-powered advisory can bridge critical gaps in access, quality, and relevance—helping more individuals unlock their career potential.

References

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Copyright

Copyright © 2025 Pratham Shenoy, Roshan Shiroorkar, Adarsh Samani. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.