How do you implement request queuing and priority scheduling for a shared AI inference service?
Under load, a shared inference service must decide whose request runs now. The signal is queuing with priorities, backpressure, and fairness wired into batching, not first-come-first-served until the service falls over.
Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.
Under load, a shared inference service must decide whose request runs now. The signal is queuing with priorities, backpressure, and fairness wired into batching, not first-come-first-served until the service falls over.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.