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Amazon interview notes, page 23 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·Hiring Manager Screen

Apr 2026
Interviewed for a PM role at Amazon, just the one question about how I'd define the role itself.
  • How would you define the role of a product manager?

“Felt deceptively open-ended.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon SWE interview with two algorithmic problems back to back. Both were more math-flavored than I expected, especially the first one. Not your typical LeetCode grind session.
  • You're given a positive-integer array A of length n. You can freely choose any integer array B of the same length. Define C[i] = B[i] mod A[i]. What is the maximum number of distinct values C can contain, and how do you compute that maximum efficiently? Give time and space complexities.
  • Given two lowercase strings s and t, you can pick one letter in each string (independently) and delete any number of occurrences of that letter. After doing this, can s and t become anagrams of each other? Design an algorithm and analyze its complexity.

“This one took me a minute to even parse what they were asking.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

Apr 2026
System design round at Amazon for a software engineering role, focused entirely on database high availability. The whole session was about primary-replica failover: detection, orchestration, recovery, the works. Pretty intense if you haven't thought deeply about replication semantics before.
  • Design a high-availability failover system for a primary-replica relational database. Cover how you detect primary failure, promote a replica with minimal downtime and bounded data loss, and return the system to a healthy state.
  • What RPO is acceptable for this system, and how does that choice affect your replication mode selection?
  • How do you avoid split-brain when detecting primary failure? What prevents two nodes from both believing they are the primary?
  • Among multiple replicas, how do you decide which one to promote after the primary goes down?
  • How do you handle downstream consumers of the replication stream, like CDC pipelines or search indexers, when a failover happens and the log position changes?
  • A replica that was lagging by 8 seconds gets promoted. What exactly is lost, how do you detect it, and what do you tell affected clients?
  • How would you extend this design to support multi-region disaster recovery, and what new consistency trade-offs does WAN replication introduce?

“This is the main question and it's a lot.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon SWE coding round centered on LRU Cache, which sounds manageable until you realize they want the full doubly-linked-list plus hashmap implementation and will steer you away from language shortcuts. The interviewer was clearly testing whether you understood the data structure, not just whether you could produce working code.
  • Implement an LRU cache with O(1) get and put operations. On capacity overflow, evict the least recently used key. A get counts as a use.

“My first instinct was to reach for OrderedDict and call it a day.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Behavioral prep material for an Amazon SWE internship, covering personal and team challenges plus the classic motivation question. Nothing technically surprising but the leadership questions have some teeth if you haven't thought them through.
  • Tell me about a significant challenge you faced at work or school and how you handled it.
  • Describe a time your team ran into a serious problem. How did you keep people motivated and push toward a solution?
  • Why do you want to work at Amazon specifically?

“I structured it as situation, action, result and it came out okay but I leaned too hard on the setup and rushed the resolution.”

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Amazon·Software Engineer·Online Assessment (OA)

Apr 2026
Amazon OA for a SWE role. One algorithmic problem, the kind where the setup takes longer to read than the actual solution probably should. Left feeling uncertain about edge cases.
  • Given an array of warehouse capacities and a list of shipments each requiring a minimum main warehouse capacity and a minimum combined backup capacity, find the minimum tokens (each token adds 1 unit of capacity to any warehouse) needed per shipment. Costs reset between shipments, and excess main warehouse capacity cannot spill over into the backup total.

“The problem statement is dense.”

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Amazon·Software Engineer·Technical Phone Screen

Apr 2026
Amazon SWE coding round, one question the whole time. Pretty focused session, they wanted both a working solution and a complexity breakdown so it wasn't just about getting the answer.
  • Given a sorted (non-decreasing) integer array and a target value, return all unique index pairs (i, j) where i < j and the two elements sum to the target. Duplicates should not produce repeated pairs. Walk through your approach and analyze the time and space complexity.

“Two pointers was the right call and I knew it immediately, but I fumbled the duplicate-skipping logic for a bit.”

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Amazon·Machine Learning Engineer·Onsite - Behavioral / Leadership

Apr 2026
Went through the Amazon behavioral loop and came out with a much clearer picture of how deep they actually go on leadership principles. Every round had a solid chunk of behavioral questions, and the follow-up drilling is no joke. If you think one good story per principle is enough, it isn't.
  • Tell me about a time you were working against a tight deadline with multiple things happening at once.
  • Describe a conflict you had with a peer and walk me through how you resolved it.
  • Tell me about a time you took on work that was outside your defined responsibilities.
  • Walk me through a time you received tough feedback. How did you respond to it?
  • Tell me about a time you gave difficult feedback to someone.
  • Describe a situation where you disagreed with a decision but ultimately committed to it and delivered.
  • Tell me about a risky decision you made when you didn't have all the information you needed.
  • Walk me through a time you had to make a fast decision under ambiguity.
  • Pick a project and go deep on it. Bring numbers.

“This one sounds easy until you're three follow-ups deep and the interviewer wants to know the exact tradeoff you made between two workstreams.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Amazon system design follow-up round, focused entirely on caching layer design for an existing implementation. Pretty dense question with eight sub-parts, felt like a written exam more than a conversation.
  • Given an existing implementation that repeatedly resolves file paths or parses license strings, propose and fully analyze adding an in-memory dictionary-backed cache. Cover where to cache, key/value design, expected hit rate, eviction policy, invalidation strategy, concurrency safety, pseudocode for get/put with validation, and time/space complexity before and after.

“Eight parts.”

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Amazon·Data Scientist·Technical Phone Screen

Apr 2026
Amazon data scientist interview focused on visualization fundamentals, which sounds easy until you realize how much nuance they expect around when and why you'd pick a given chart type.
  • What is a pie chart, and when should you use or avoid it?
  • Which graph types are most useful during exploratory data analysis, and what makes them effective?
  • How would you use a graph to explore the relationship between two variables?

“I gave the textbook answer about part-to-whole composition, but stumbled when pressed on when NOT to use one.”

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