CareerVault: Smart Job Tracker

CareerVault 🚀

Tired of losing track of job applications and feeling overwhelmed? CareerVault organizes your job search and gives you peace of mind. Unlike Excel or Notion, CareerVault is built specifically for job seekers, offering easy interview scheduling, progress tracking, and instant export of application history. With AI-powered interview preparation, CareerVault helps you stay on top of your career journey.

Inspiration

I was inspired to build CareerVault because job hunting can be chaotic and stressful. I wanted a tool that not only tracks applications but also prepares you for interviews, all in a single, easy-to-use platform. Unlike generic tools like Excel or Notion, CareerVault is purpose-built for job seekers, saving time and reducing mental load

How I Built It

Frontend: Created a responsive UI with React, TypeScript, and Tailwind CSS for a clean and intuitive dashboard.

Backend & Database: Used Firebase Authentication for user login and Firestore for storing applications and interview data.

AI Integration: Leveraged OpenAI API to generate interview questions and tips for each role.

Progress Visualization: Implemented charts with analytics formulas to help users see trends in their job search.

Export Functionality: Built CSV and PDF export to give users full control over their application history..

Challenges & Lessons Learned

AI Integration: Integrating OpenAI for interview suggestions was tricky. Handling dynamic prompts and context required iterative testing.

Next Steps

Fix the notification system to alert users for upcoming interviews.

Improve AI prompts for more role-specific interview preparation.

Add analytics dashboard enhancements for deeper insights into job application trends.

Notification System: Implementing notifications for interview reminders and status changes was challenging. I plan to fix this in the GitHub updates.

Data Syncing: Ensuring that the dashboard updates in real-time when users change application statuses required careful Firestore rules and listeners.

Lesson Learned: Building a full-stack, AI-enabled app taught me how to bridge frontend, backend, and AI seamlessly, and reinforced the importance of iterative testing and user feedback.

Built With

• ai/ml:
• api
• backend
• built-with-frontend:-react
• control:
• css
• database:
• design
• firebase
• firestore)
• git
• github
• interview
• openai
• preparation
• tailwind
• tools:
• typescript
• version
• vite