AI video generation looks simple from the user interface: enter a prompt, upload an image, wait a bit, and get a video. The backend is not that simple. If you are building a product that calls an AI video API, you need to handle long-running jobs, retries, provider callbacks, file storage, user-facing status, and review before anything gets published. This article walks through one practical architecture for that workflow. I will use SeeVido as an example of the kind of external AI video service a product might call, but the pattern applies to any provider that accepts prompt-to-video or image-to-video requests. The Problem: Video Generation Is Not a Normal Request Most web requests are short. A user clicks a button, your server does some work, and the response comes back quickly. AI video generation is different. It can take time, fail halfway, produce an output that needs review, or return a callback after the user has left the page.…