## Inspiration

Job searching is often fragmented across job boards, resumes, GitHub, applications, and calendars. CareerPilot was built to bring these pieces together into one AI-powered career workspace that helps candidates make better decisions instead of simply applying everywhere.

What it does

CareerPilot analyzes a user's career profile and evaluates job opportunities based on skills, experience, projects, and career goals. It can discover jobs, score opportunities, track applications, analyze GitHub projects, and help organize follow-up actions.

How we built it

The backend is built with Python and FastAPI, with an agent-based architecture for career analysis and decision-making. The frontend uses React and Vite. The application supports real API integrations including GitHub, Google OAuth for Gmail and Calendar, and Adzuna for job discovery. Local development uses a lightweight local storage backend, while the architecture also supports AWS services for production deployment.

Challenges

One of the biggest challenges was designing the system so that AI recommendations remain useful and explainable rather than becoming a simple chatbot. We also had to handle authentication, API integrations, local development, external services, and deployment while keeping the application modular.

What we learned

We learned how to combine AI agents with real-world APIs and career data, while building reliable authentication, integrations, and backend services. The project also gave us practical experience connecting a React frontend with a FastAPI backend and designing an architecture that can evolve from local development to cloud deployment.

What's next

Future improvements include stronger job matching, deeper GitHub analysis, better application automation, richer career insights, and additional integrations to make CareerPilot a complete career management platform.

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