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Amazon interview notes, page 13 of 159

FAANG / Big Tech

Most of these Amazon write-ups come from Software Engineers (1,092), then Data Scientists (182) and Product Managers (165). The most reported rounds are the technical phone screen (618), the behavioral / leadership round (309), the online assessment (228) and the system design round (159).

1581 interview notes · updated Oct 2026

Amazon·Software Engineer·Onsite - Coding / Algorithms

Apr 2026
Amazon SWE coding round with a string manipulation problem that had a greedy twist to it. Nothing too wild but the optimization angle took me a second to see clearly.
  • You're given a string containing '0', '1', and '!' characters. Each '!' can be independently replaced with '0' or '1'. After substitution, every '10' subsequence contributes x errors and every '01' subsequence contributes y errors. Return the total error count modulo 10^9 + 7. (Variant: minimize or maximize the total.)

“My first instinct was to try all combinations of replacements which is obviously wrong the moment you think about input size.”

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Amazon·Machine Learning Engineer·Hiring Manager Screen

Apr 2026
Hiring manager screen for an MLE role at Amazon. Pretty conversational, more about how you think than grinding through code. The big technical question was around model degradation in production and it took up most of the time.
  • Your model performs significantly worse in production than it did during offline evaluation. Walk me through how you would diagnose and fix this.

“This is the kind of question that sounds manageable until you're actually in it and realize how many directions it can go.”

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Amazon·Product Manager·Onsite - Behavioral / Leadership

Apr 2026
Amazon PM interview with a behavioral question that had some real teeth to it. The kind of question that sounds straightforward but forces you to think about ownership and organizational politics at the same time.
  • Tell me about a time you took on a problem that others had avoided or decided wasn't their responsibility.

“This one tripped me up a little because my first instinct was to frame it as a heroic solo effort, which felt off.”

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Amazon·Product Manager·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round at Amazon for a PM role, pretty standard leadership principles territory. Just the one question but it required a real story, not a vague answer.
  • Tell me about a time your work was criticized.

“I had a story ready but it was too safe, like 'someone gave me minor feedback and I fixed it.' I could tell partway through they wanted something with more weight to it.”

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Amazon·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Amazon ML Engineer screen that mixed a deep dive into past internship work with some LLM fundamentals and behavioral questions. Nothing too wild but the combo kept you on your toes.
  • Walk me through a project you worked on during a previous internship.
  • What are the core concepts behind large language models and how do they work?
  • Tell me about a time you faced a challenge working with a team or stakeholder.

“Expected this but still fumbled the pacing a bit.”

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Amazon·Technical Program Manager·Onsite - System Design / Architecture

Apr 2026
Amazon TPM interview that leaned heavily on system design. One meaty question about a program I'd managed, and they wanted the full picture, not just a high-level sketch.
  • Walk me through the design and architecture of a program you've managed. Cover it end-to-end and explain why you chose the technologies you did.

“This one exposed me a bit.”

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Amazon·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Amazon PM interview with a product design question about vending machines for hotels and motels. Pretty open-ended and I had to keep reminding myself to stay structured instead of just listing features.
  • You're a PM at a vending machine company. Design a new line of vending machines specifically for hotels and motels.

“I jumped straight into features and had to walk it back.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Interviewed for a business analyst role at Amazon, behavioral focus, one question that sounds easy until you're actually in the room trying to remember a good example on the spot.
  • Can you describe a situation where your analysis directly shaped a business decision?

“I had an answer prepped but it felt thin the moment I started telling it.”

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Amazon·Software Engineer·Online Assessment (OA)

Apr 2026
Amazon SWE online assessment with a greedy/heap problem that looks straightforward but has a nasty edge case around large m values. The math shortcut is the whole game here.
  • You have n VM types each with an initial inventory count. Process m rental requests one at a time: each request picks the VM type with the highest current inventory, earns revenue equal to that inventory value, then decrements it by 1. Compute total revenue across all m requests.

“First instinct was just throw a max-heap at it and simulate.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon SWE coding round with a twist on the classic word search problem. The modification allowing diagonal movement and cell reuse changes the problem enough that you can't just pull your standard solution from memory.
  • Given a 2D grid of characters, determine whether a given word can be formed by traversing sequentially adjacent cells, where adjacency includes diagonal neighbors and cells can be reused. Implement exist(grid, word) -> bool.

“The diagonal part tripped me up at first because I had the standard 4-direction version basically memorized.”

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