I recently built Job Board

I recently built Job Board Hub, a MERN stack application that helps users discover remote job opportunities across different areas like technology, design, marketing, and more.

The idea is simple: job descriptions are often too long, repetitive, or hard to scan quickly. So I integrated an AI-powered job summary feature that allows users to generate a quick summary of each position and understand faster whether the role fits their profile.

But beyond the UI, this project was focused on demonstrating important backend decisions that are often overlooked.

The AI integration was built through an AI Gateway, making the system flexible enough to change models over time or even combine different providers in the future. I also implemented rate limiting to prevent abuse, protect token usage, and control costs.

Another key detail is the use of streaming responses, which improves the user experience by showing the AI summary progressively instead of waiting for the entire response to finish.

Some backend highlights:

- MERN stack application - AI Gateway architecture - AI-powered job summaries - Streaming responses for better UX - Rate limiting to protect API usage - Clean backend structure for scalability - Remote jobs organized by category:

This project helped me explore how AI can be integrated into real product experiences while keeping backend performance, scalability, and cost control in mind.

Job Board Hub is not just a job listing app — it’s a small example of how AI can make everyday platforms faster, clearer, and more useful.