Meta Software Engineer Interview Questions

Before designing it, I would clarify whether permissions are role-based, resource-based, or both. My default approach would be to use a combination of roles, groups, and fine-grained access checks so the system stays flexible as the product grows. I would keep authorization logic separate from the business logic so permissions are easier to audit and change. The trade-off is between simplicity and control, and at scale I would usually prefer a clear policy layer rather than scattering checks across the codebase. I would also think about caching permission decisions, revocation speed, and audit logging.

Situation: We had a recurring performance issue, but the fix required changes from both backend and frontend teams. Task: I needed to align the teams on a solution even though I was not the manager or official owner. Action: I gathered a small amount of data, showed where the time was actually being spent, and proposed a minimal change that reduced work for both teams. I kept the discussion focused on user impact and effort instead of blaming any side. Result: Both teams agreed to the plan, we shipped the fix in the next sprint, and response times improved noticeably.

Situation: I was working on a caching change that involved several trade-offs around freshness, latency, and failure behavior, and not everyone on the team was comfortable with the details. Task: I needed to explain the change in a way that product and engineering teammates could both follow. Action: I used a simple diagram, described the old and new flow in plain language, and compared the two options using a few concrete examples instead of a long technical lecture. I also highlighted the user-facing impact so the reasoning was easier to connect to the product goal. Result: The team aligned quickly, the decision was approved, and the rollout went more smoothly because everyone understood the risk.

I would first think about sorting both arrays and using two pointers, but if I care about speed I would usually use a hash set. I would put the smaller array into a set and then scan the larger array, adding elements that appear in both. The reason I choose a hash set is that it gives O(n) average time and keeps the implementation simple. If duplicates matter, I would adjust the data structure to track counts instead of just membership. I would also mention edge cases like empty arrays and whether the result should be unique or preserve duplicates.

I would first clarify whether the feature flags are meant for experimentation, gradual rollout, emergency kill switches, or all of the above. At a high level, I would have a central config service store flag definitions, target rules, and rollout percentages, and application servers would cache those flags locally for fast evaluation. The reason I prefer cached evaluation is that feature checks happen on the request path and must stay lightweight. I would also think about audit logs, rollbacks, and how to avoid stale flags lingering forever. The trade-off is between flexibility and operational complexity, so I would design it to be easy to use but still safe to manage at scale.