Your question is Robust A/B Testing for Scale. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How would you design a robust A/B test for a large-scale product decision at Google?
Explain how you would define the estimand and primary metric, randomize users, calculate sample size and test duration, analyze the result, and decide whether to launch. Address interference, sample-ratio mismatch, repeated looks, multiple metrics, heterogeneous treatment effects, and guardrail metrics. State the assumptions you would verify and how you would respond if they failed.