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Amazon interview notes, page 7 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·Technical Phone Screen

Apr 2026
Did a technical interview for a SWE role at Amazon. One question about past project challenges, pretty standard stuff.
  • Tell me about a technical challenge you encountered in a previous project and how you handled it.

“Pretty open-ended.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon SWE interview with a pretty gnarly algorithmic problem centered on sliding window medians. The problem had enough moving parts that it took me a while to even see the full shape of it.
  • Given a continuous stream of product reviews, design a data structure that efficiently returns the median rating of the most recent N reviews at any point in time. When a new review comes in and the window is full, the oldest review should be evicted. Target O(log N) per update.

“The median-of-a-stream part I knew cold, two heaps, keep them balanced, done.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon SWE coding round, one problem the whole time. Parentheses stuff with a twist I wasn't fully prepared for.
  • Given a string of parentheses types and an array of their associated efficiency ratings, write a function that finds the most efficient valid parentheses sequence you can form and returns its total efficiency score.

“I knew it was a DP or stack problem the second I read it, but the efficiency rating layer threw me off.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round at Amazon for a software engineering role. The whole thing was basically one question stretched across however long they wanted to go, with follow-ups that kept peeling back layers until you ran out of story.
  • What's the biggest challenge you've faced, and walk me through exactly how you handled it, including how you identified solutions, where you got stuck, who you asked for help and how, and what you'd do differently?

“The question itself sounds manageable until the follow-ups start and you realize they want the full autopsy, not the highlight reel.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Amazon SWE interview, system design round. Just the one question about Kubernetes internals, which felt like it could go pretty deep depending on how the conversation went.
  • What is the difference between the Kubernetes control plane and the data plane?

“I knew the broad strokes but fumbled the specifics under pressure.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon Research Scientist coding screen, one algorithm question and then some discussion about how you'd extend it. Pretty straightforward but the follow-up conversation about streaming variants was where things got interesting.
  • Given a string, find the index of the first character that does not repeat anywhere else in the string. Return -1 if no such character exists.

“Two-pass approach, count all characters first then scan again for the first one with a count of exactly one.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon SWE interview with a pretty involved question about real-world generative AI usage. One question but it had a lot of surface area to cover, felt more like a system design plus responsible-AI conversation rolled into one.
  • Walk me through a project where you used generative AI tools (like LLMs, code assistants, or image/text generation) as part of your actual workflow. Cover the problem you were solving, why you chose the specific tool, how you validated the output, what limitations you hit, the eventual impact, and any responsible-AI concerns like hallucinations, IP issues, or data privacy.

“This question has way more parts than it looks like at first.”

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Amazon·Software Engineer·Onsite - Multi Round

Apr 2026
Went through the full Amazon SDE-1 loop and the first two DSA rounds went fine, but the Bar Raiser only lasted about 30 minutes and now I can't stop second-guessing everything. The LLD portion in round 3 was rough, and the behavioral answers in the BR felt more practical than polished. Still waiting and genuinely unsure what to make of it.
  • Describe a significant challenge you faced at work and how you handled it.
  • Walk me through how you approached root cause analysis on a past incident.
  • Tell me about a time you took ownership of a problem that wasn't strictly yours to fix.
  • How have you handled receiving critical feedback, and what did you do with it?
  • Describe a situation where you had to quickly learn a new technology to get something done.

“I pulled from production support work, talked through a workflow failure I investigated by digging into logs and comparing successful runs against broken ones.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round at Amazon for a SWE role, just the one question about handling difficult news. Pretty standard leadership principles territory.
  • Tell me about a time you received difficult news from a peer or manager.

“I went with a story about a project getting scoped down last minute and how I had to adjust.”

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Amazon·Product Manager·Onsite - Behavioral / Leadership

Apr 2026
Behavioral screen for a PM role at Amazon, basically one question deep into the leadership principles territory. Short but the kind of question that can unravel you if you haven't actually lived through a real miss.
  • Tell me about a time you knew ahead of time that you weren't going to hit a goal.

“This one tripped me up more than I expected.”

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