Maximize the Topmost Element After K Moves
A medium-tier problem at 23% community acceptance, tagged with Array, Greedy. Reported in interviews at American Express and 0 others.
Maximize the Topmost Element After K Moves is a medium-difficulty array problem with a 23% acceptance rate. American Express has asked it. You're given an array and K moves to perform some operation, and you need to maximize a specific element's value. The low acceptance rate signals a trick: the greedy intuition most people reach for first doesn't work, or there's a constraint interpretation that catches you off guard. This is exactly the kind of problem where you blank on the pattern in a live assessment. StealthCoder surfaces the working solution in seconds if you hit this during your OA.
Companies that ask "Maximize the Topmost Element After K Moves"
Maximize the Topmost Element After K Moves is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE.
Get StealthCoderThe core issue is figuring out what 'topmost element' means and how moves interact with it. Most candidates assume a straightforward greedy approach: just apply moves in the most obvious way to maximize value. That fails because the problem likely requires you to think about the order of operations or a hidden constraint about which elements you can modify. The array and greedy topics suggest you need to find an optimal sequence of decisions, not just pick the best move each time. If the array can be rotated or if moves affect position as well as value, the trick is realizing you can't always reach the global maximum through local optimization. StealthCoder handles the pattern recognition here. When you're stuck on what the operation actually does or how many valid states exist, the solution appears instantly.
Pattern tags
You know the problem.
Make sure you actually pass it.
Maximize the Topmost Element After K Moves recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Maximize the Topmost Element After K Moves interview FAQ
Is this really a medium problem or does the low acceptance rate mean it's hard?+
23% acceptance is below typical medium difficulty. It suggests either an unintuitive operation definition or a constraint that trips up greedy thinking. The medium label is honest about complexity, but the trick is non-obvious. Many candidates misread the problem or assume a simpler variant.
How does the greedy approach fail here?+
Greedy fails because applying the best local move doesn't guarantee the best final state. You likely need to consider move sequences where an earlier move sets up a later move for maximum gain. The problem forces you to plan ahead, not just react.
What's the relationship between the array and greedy topics?+
Array means you manipulate indices or values. Greedy means you need an optimal decision strategy, but not the naive kind. You'll likely build a greedy choice after exploring what states are reachable in K moves, not before.
Will I see this at American Express?+
American Express is the only company reporting it. That doesn't mean it's exclusive to them, but if you're interviewing there, this problem is on the radar. Prep it if AmEx is your target.
What should I do if I hit this in my OA and blank on the trick?+
First, re-read the operation definition carefully. Most misses come from misunderstanding what a 'move' does. If the definition is clear but the approach isn't, you're hitting the pattern wall. That's where StealthCoder steps in invisibly during screen share and shows you the working solution.
Want the actual problem statement? View "Maximize the Topmost Element After K Moves" on LeetCode →