AI Career Coach: A Full-Stack Intelligent Web Application for Personalized Career Development in the AI Domain

Abstract

The modern AI job market presents significant challenges for both aspiring and experienced professionals — from identifying relevant skills and understanding emerging industry trends to preparing for technical interviews and crafting impactful application materials. Traditional career coaching methods and existing online platforms, while helpful in certain respects, lack the integration, personalization, and AI-driven intelligence required to effectively guide individuals through the complex AI career landscape. This paper presents the AI Career Coach, a comprehensive, full-stack intelligent web application designed to empower individuals at every stage of their AI career journey — from beginners entering the field to seasoned professionals seeking advancement. The platform is built upon a modern technology stack comprising Next.js for a performant server-rendered frontend and backend, Neon DB as a serverless PostgreSQL database, Prisma as a type-safe ORM for streamlined data management, Tailwind CSS and Shadcn UI for a consistent and accessible user interface, and Inngest for reliable scheduled background task processing. At its intelligence core, the platform integrates Google's Gemini AI API to deliver dynamic and personalized career guidance. Key functionalities include a personalized onboarding and profile management module, an AIgenerated industry insights engine, an AI-powered mock interview generator with performance analytics, an AIassisted resume builder with Markdown generation and PDF export, and a contextual cover letter generator. The system architecture follows a modular and iterative Agile development approach, emphasizing scalability, developer productivity, and seamless AI integration. Testing encompassed functional validation, performance evaluation of API endpoints, and security hardening through input validation, CSRF protection, and HTTPS enforcement. The platform demonstrates how modern fullstack development paradigms can be effectively combined with large language model APIs to create practical, highimpact AI-driven applications.