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Amazon interview notes, page 86 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·Online Assessment (OA)

May 2026
Took the Amazon AI coding OA and found it pretty manageable, mostly because I'd worked with Node.js before and could spot the controller/route issue pretty quickly. Finished in under 40 minutes. The main tip I'd pass along is that the practice test Amazon sends you is genuinely close to the real thing, which I didn't fully appreciate until after.
  • Debug a broken Node.js application by identifying and fixing issues in the controllers and routes.

“Prior Node.js experience made this click fast.”

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Amazon·Data Scientist·Technical Phone Screen

May 2026
Amazon Data Scientist interview with a deep technical problem-solving question. The format pushed you to walk through a real past project end-to-end, not just describe what you built but why you made the calls you did.
  • Walk me through a complex technical problem you personally solved. What was the situation, what options did you consider, what trade-offs did you weigh, and what actually happened in the end?

“This is the kind of question that sounds easy until you're in it and realize your example isn't landing.”

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Amazon·Software Engineer·Online Assessment (OA)

May 2026
Amazon OA for a SWE role, just one coding problem about sorting error codes by frequency. Pretty straightforward on the surface but easy to get the tie-breaking logic wrong if you rush.
  • Given an array of integer error codes, sort them so that less frequent codes appear first. If two codes have the same frequency, the smaller numeric value comes first. Return the full sorted array including duplicates.

“I went straight for a frequency map and then sorted by (freq, value).”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Amazon SWE behavioral round, basically one big question about a project failure. Not a lot of back and forth, just dig in and keep going deeper.
  • Tell me about a project that went seriously wrong. What were you trying to do, what broke down, what was your role in it, and how did the team recover? Walk through the root causes across technical, process, and communication dimensions, and what specifically changed about how you work after.

“This one has layers and I underestimated that going in.”

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Amazon·Machine Learning Engineer·Onsite - System Design / Architecture

May 2026
Amazon ML Engineer interview that was basically a two-part system design session. Part one was a classic LFU cache implementation with an O(1) constraint, part two went into distributed streaming territory which I was not expecting at all.
  • Design and implement an LFU cache with O(1) time complexity for both get and put operations. Walk through the data structures you'd use and how eviction works when multiple keys share the lowest frequency.
  • How would you extend the LFU concept to a distributed, high-volume data stream across many machines where you can't store exact counts? What approximate data structures would you use per node, and how do you merge them globally?
  • In the distributed streaming setting, how do you handle late-arriving or out-of-order events, and how would you implement time-based decay so that recent accesses matter more than old ones?
  • What are the trade-offs between accuracy, memory usage, and latency in your distributed frequency tracking design, and how would you justify the choices you made?

“I knew LRU cold but LFU tripped me up at first because the tie-breaking rule (least recently used among the least frequent) means you need two layers of ordering.”

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Amazon·Software Engineer·Recruiter / HR Screen

May 2026
Amazon recruiter screen for a software engineer internship role, basically just logistics and availability questions. Nothing technical, pretty standard stuff.
  • How long can you commit to this internship (3, 6, or 12 months), what start date works for you, and are you open to converting to a full-time role after? Also, do you have any constraints around school schedule, visa status, or location?

“Pretty much just a logistics check.”

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Amazon·Data Scientist·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Amazon for a Data Scientist role. The question was scenario-based and felt more like a soft skills probe than anything technical, but it had more layers than I expected once I started answering.
  • Your analysis produces a result that contradicts what the rest of the team believes to be true. How do you handle it?

“I started by talking about re-checking the work, which felt obvious and a bit defensive in retrospect.”

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Amazon·Software Engineer·Online Assessment (OA)

Jun 2026
Applied for an Amazon SDE new grad role, got the OA a few months later, completed all three parts with visible tests passing, and still ended up archived two days after submitting. No rejection email, no explanation.
  • Does Amazon reject candidates after a passing OA due to work-style assessment results, hidden test cases, code quality signals, or headcount constraints?
  • Does submitting an OA close to the time limit negatively affect the evaluation outcome?

“This is what's eating at me.”

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Amazon·Software Engineer·Online Assessment (OA)

Jun 2026
Amazon SWE coding round, one question about counting special substrings in a DNA string. Pretty clean problem once you see the pattern, but I fumbled around longer than I should have before the structure clicked.
  • Given a DNA sequence string, count all substrings that are either exactly 2 identical characters, or longer substrings where the first and last characters match and the middle portion consists of exactly one distinct character.

“Took me a while to even parse what 'special' meant here.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Amazon behavioral loop for a software engineer role, basically a full hour of leadership principles questions with a lot of follow-up probing to make sure you weren't just making things up. No technical depth tested at all, which surprised me a bit.
  • Tell me about a time you had a conflict with a peer, manager, or cross-team partner and how you handled it.
  • Walk me through a situation where you had to dig deep to find the actual root cause of a problem, not just the surface symptom.
  • Describe a time you took action or ownership beyond what your role formally required.
  • Give me a recent example of how you've used generative AI tools in your day-to-day work.

“They asked this three separate times across different relationship types, which I wasn't ready for.”

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