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Amazon interview notes, page 19 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·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
PM interview at Amazon with a product sense question about improving an existing feature. Pretty standard stuff but the scope of the question is deceptively wide if you're not careful about where you focus.
  • How would you improve shipment tracking on Amazon?

“I went straight into listing features and kind of lost the plot for a few minutes.”

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Amazon·Software Engineer·Online Assessment (OA)

Apr 2026
Amazon OA for a SWE role, just one algorithmic problem about maximizing server memory capacity. Pretty clean problem once you see the pattern, but I overthought the pairing logic at first.
  • Given an array of memory capacities for n servers (always an even number), split them into equal groups of primary and backup servers such that every primary has a backup with at least as much memory. Maximize the total memory of all primary servers.

“Took me a minute to see it.”

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Amazon·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Amazon interview focused on unsold products. Not enough detail in the source to say much more than that.
  • How would you address the problem of unsold products on Amazon's platform?

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon embedded software interview with a pretty gnarly system design question about heterogeneous multicore scheduling. Not the typical LeetCode grind, more of an open-ended architecture discussion that left me second-guessing myself for a while after.
  • You have a non-symmetric multiprocessor system where some cores only handle division and others have hardware acceleration for both multiplication and division. Given a batch of vectorized arithmetic operations, how would you design an algorithm to assign operations to cores for near-optimal total execution time? Walk through your cost model, heuristic choices, and the trade-offs involved.

“This one took me a second to even parse.”

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Amazon·Software Engineer·Onsite - Multi Round

Apr 2026
Four rounds at Amazon for an SDE-1 role: two DSA rounds, a GenAI hybrid round that barely has any prep material online, and a Bar Raiser that ended in rejection. Cleared the first three but stumbled on the Bar Raiser's coding problem and needed hints, which probably sealed the fate. The wait afterward was brutal, over a month of vague recruiter replies before the rejection landed.
  • Given a grid of oranges where some are rotten, how long does it take for all fresh oranges to rot? (Rotten Oranges / BFS grid problem)
  • Given a list of courses with prerequisites, return a valid ordering to complete all courses, or indicate it's impossible. (Course Schedule II)
  • How many ways can you tile a 2xN board using 1x2 dominoes and L-shaped trominoes? (Domino and Tromino Tiling)
  • Describe how you use AI tools in your day-to-day work, and what limitations you've run into.
  • What causes LLMs to hallucinate, and how would you go about validating outputs from a generative AI system?
  • What is prompt engineering and what techniques have you used or know of?
  • Given a number, find the next permutation of its digits in lexicographic order.
  • Tell me about a time you took full ownership of a project or problem beyond what was expected of you.
  • Describe a situation where you went unusually deep into a technical problem to understand the root cause.
  • Given a list of people and a matrix of 'knows' relationships, find the celebrity: someone everyone knows but who knows nobody. (Celebrity Problem variant)

“Pretty clean round for me.”

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Amazon·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Got a product question about Alexa shopping at Amazon, pretty open-ended stuff. Not much to go on from the interview itself but the question was meaty enough to chew on for a while.
  • What features would you build to improve the future of shopping through Alexa?

“This is the kind of question where you can go in a dozen directions and end up nowhere.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon SWE coding round, pretty much one meaty array problem with a couple verbal follow-ups tacked on at the end. Nothing too wild but the in-place constraint is where people tend to slip up.
  • You're given two sorted ascending integer arrays. The first array has extra space at the end to fit all elements of the second. Merge the second array into the first in-place so the result is sorted, using O(1) extra space.
  • How would you approach the same merge if both arrays were sorted in descending order instead of ascending?
  • If the two arrays were completely unsorted, what strategy would you use to merge them? You're allowed to modify the input arrays.

“The key move is starting from the back of both arrays and filling arr1 from the right.”

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Amazon·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Amazon PM interview with a single product design question focused on the automotive sales space. Pretty open-ended, which sounds fun until you're actually in it.
  • Design a product that helps automotive salespeople close more deals.

“I went straight to CRM-adjacent ideas and kind of anchored myself there too fast.”

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Amazon·Software Engineer·Online Assessment (OA)

Apr 2026
Amazon SWE online assessment with two coding problems. Both were algorithmic and required some careful greedy thinking. Nothing behavioral, just straight problem solving under a timer.
  • Given an array of city populations and a binary string indicating which cities have security units, you can optionally move each unit one position to the left. A city is protected if it has at least one unit after all moves. Maximize the total population of protected cities.
  • Given a binary array and an integer k, repeatedly choose a subarray of length exactly k, pay a cost equal to its current sum, then zero out exactly one element in that subarray. Find the minimum total cost to zero out the entire array.

“The greedy angle here is that you scan left to right and decide whether moving a unit left gains you more population than keeping it in place.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon Applied Scientist interview focused heavily on ML evaluation metrics, but don't let the coding part fool you. The real test was the conceptual discussion around when and why you'd use each metric, and I felt underprepared for how deep they wanted to go on the tradeoffs.
  • Implement precision, recall, ROC curve, and AUC from scratch given true labels and predicted scores.
  • When does precision matter more than recall, and when is it the other way around?
  • Why is AUC considered threshold-independent, and what are its limitations?
  • How do precision, recall, and F1 behave under class imbalance, and when would you prefer PR-AUC over ROC-AUC?
  • How does the ROC curve relate to the cost tradeoff between false positives and false negatives?

“The code itself wasn't the hard part.”

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