Abstract: The contemporary job market has become increasingly complex, creating a powerful demand for smart systems that offer individualized career guidance. Common methods of career support are unsuccessful in adapting to personal requirements and rapidly changing skill needs. To address this challenge, this paper proposes AUTONIX, a modular career intelligence platform integrated with AI, aimed at providing scalable and flexible employability support.
The proposed system leverages Large Language Models (LLMs) to perform tasks including resume optimization, interview simulation, cover letter generation, and industry trend analysis. The platform is based on a full-stack architecture incorporating modern technologies such as Next.js for the frontend, Prisma ORM and NeonDB for data management, Clerk for secure authentication, and Inngest for asynchronous workflow processing.
Structured prompt engineering is a core feature of the system, ensuring that AI-generated outputs are context-aware, consistent, and aligned with user requirements. By utilizing the Gemini API, the system transforms unstructured inputs such as resumes and job descriptions into actionable and insightful information.
Experimental results demonstrate that AUTONIX produces high-quality, role-specific, and ATS-compatible outputs while maintaining system stability and responsiveness. The platform advances the application of AI-based career advisory systems and contributes to the development of scalable, intelligent, and real-world-deployable career guidance solutions.

Index Terms: Artificial Intelligence, Career Guidance System, Full-Stack Architecture, Large Language Models, Resume Optimization.

Downloads: | DOI: 10.17148/IARJSET.2026.13469