← Amazon Interview Insights

Amazon·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Amazon SWE coding round, one meaty algorithmic problem that took up most of the session. The problem looked like a stack question on the surface but the exact semantics tripped me up at first.

Questions Asked (1)

Q1

Given an array of integer task priorities where tasks execute right to left, for each index i find the largest index j > i where priorities[j] is strictly less than priorities[i]. The delay time for index i is j - i; if no such j exists, the delay time is 0. Return the full delay time array. You must do better than O(n^2), explain your data structures, analyze time and space complexity, handle duplicates, and handle large inputs.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The 'rightmost' part is what got me.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Clarify the problem and edge cases, then propose a monotonic stack solution that processes the array from right to left to find the nearest smaller element to the right. Explain how the stack maintains indices of potential candidates, and analyze time and space complexity as O(n).

Pro tip: Emphasize that the monotonic stack works because we only need the nearest smaller element to the right, and any elements that are larger than the current can be discarded as they will never be the answer for earlier elements. This demonstrates deep understanding of the technique.

1. Clarify the problem and edge cases

Restate the problem in your own words, confirm that tasks execute right to left, and discuss edge cases like empty array, single element, all increasing/decreasing, and duplicates.

2. Propose a brute-force approach and its complexity

Mention that a naive O(n^2) solution would check each element against all elements to its right, but this is inefficient for large inputs.

3. Introduce the monotonic stack approach

Explain that you will traverse the array from right to left, maintaining a stack of indices with strictly increasing priorities from top to bottom (or decreasing, depending on implementation). For each element, pop elements from the stack that are greater than or equal to the current priority, then the top of the stack (if any) is the nearest smaller element to the right.

4. Walk through an example and handle duplicates

Trace the algorithm on a small example, showing how the stack evolves and how duplicates are handled (e.g., by popping equal elements to ensure strict inequality).

5. Analyze complexity and discuss scalability

State that each element is pushed and popped at most once, giving O(n) time and O(n) space. Mention that this handles large inputs efficiently and is suitable for Amazon's scale.

Key Points to Mention

  • Monotonic stack data structure and its invariant
  • Right-to-left traversal to find nearest smaller element
  • Handling duplicates by popping equal elements to enforce strict less-than
  • Time complexity O(n) and space complexity O(n)
  • Edge cases: empty array, single element, all increasing/decreasing
  • Comparison with brute-force O(n^2) and why stack is better

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.