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Amazon interview notes, page 123 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 - Behavioral / Leadership

Jun 2026
Amazon behavioral prep for an intern/early-career software engineer role, covering leadership principle themes with heavy follow-up designed to stress-test whether your stories are real. Six prompts total, ranging from conflict resolution to AI tool usage.
  • Tell me about a conflict or disagreement you had with a teammate, manager, or cross-functional partner. What caused it, how did you handle it, and what happened?
  • Describe a second conflict where priorities, timelines, or technical opinions didn't line up. How did you work through it?
  • Walk me through a conflict where you had to keep someone's trust while still pushing back on a decision you thought was wrong.
  • Tell me about a time you dug into a problem and found the actual root cause instead of going with the first explanation.
  • Describe a time you took on work that wasn't technically your responsibility because the team needed it done.
  • How have you used generative AI tools in coursework, internships, or projects? What helped, what risks did you think about, how did you verify the output, and what limits did you set for yourself?

“The follow-up pressure is where this one gets you.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Went through a behavioral round for a solutions architect role at Amazon. Just the one question but they really sat with it.
  • Describe a time when you took on a significant responsibility outside your normal scope.

“I had a decent story ready but I think I buried the lead.”

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

Jun 2026
System design round at Amazon for an ML Engineer role, and they threw a genuinely gnarly distributed systems problem at me. The scope kept expanding the more I talked, which was either a good sign or a trap I walked into myself. Not totally sure how it went.
  • Design a service that takes a list of job parameters, submits each job to an external async cluster API, tracks their statuses, and notifies the user once all jobs in the batch have completed. Walk through the full architecture including ingest, scheduling, workers, status tracking, persistence, and notifications.
  • How would you handle retries and backoff for both job submission and status check calls to the external API, and how do you ensure idempotency across retries?
  • How would you detect and handle stuck jobs, timeouts, and partial failures within a batch?
  • How would you scale this system to handle millions of jobs, and would you prefer a polling model or an event-driven callback model for status updates from the external API?
  • How would you handle job deduplication and cancellation in this system?
  • What monitoring, alerting, and observability would you build into this system?

“This one ballooned fast.”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE coding round, one graph problem that looked straightforward until I actually had to implement it cleanly under pressure.
  • Given a number of courses and a list of prerequisite pairs, return a valid order to complete all courses. If no valid order exists due to a cycle, return an empty array.

“I knew this was topological sort the second they said it.”

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Amazon·Product Manager·Onsite - Behavioral / Leadership

Jun 2026
Went through a behavioral round for a PM role at Amazon. Just the one question but it's the kind that can go sideways fast if you don't have a tight example ready.
  • Describe a situation where you accepted a short-term cost or setback in order to achieve a better long-term outcome.

“Classic Amazon leadership principle territory.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Amazon system design round, one big question about a globally distributed metadata service. The scope was wide and the consistency vs availability angle made it pretty involved.
  • Design a metadata service that operates at global scale with strict write consistency and low read latency. Your design should handle network partitions, regional outages, and support data rollback. Walk through the consistency vs availability trade-offs and how the system degrades gracefully under failures.

“I jumped straight into a quorum-based replication approach and the interviewer kept poking at what happens when a region goes dark mid-write.”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE coding round with a log processing problem. Pretty much a sliding window / timestamp filtering question dressed up as a security/anomaly detection scenario.
  • Given a list of log entries (each with a user ID, timestamp, and event type), find all users who triggered a specific event more than k times within any 24-hour window.

“My first instinct was to group by user and event then sort by timestamp, which is fine, but I initially forgot to handle the sliding 24-hour window correctly.”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE interview with a tree problem that looked clean on the surface but had enough edge cases to trip you up if you weren't careful. One question, but it had legs.
  • Given the root of a binary search tree and two keys p and q, find their lowest common ancestor. The LCA is the deepest node whose value falls between p and q inclusive. Implement both an iterative and a recursive solution, and handle cases where one or both keys might not exist in the tree.

“The base traversal logic clicked pretty fast since BST structure makes LCA navigation straightforward.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Amazon business analyst interview centered on a system design prompt about building a clickstream data pipeline, Netflix-style. Pretty technical for a BA role, wasn't expecting to go that deep into infrastructure tradeoffs.
  • How would you design a large-scale clickstream data pipeline similar to what a streaming platform like Netflix might use?

“I started with ingestion and worked toward storage and querying, which felt logical but I think I spent way too long on the front end of the pipeline and never got to the analytics layer in a satisfying way.”

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Amazon·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Amazon product sense interview, just the one question about gifting. Not a lot of context to go on but it's a meaty enough topic that it could easily eat up 45 minutes if they push you on it.
  • How would you improve the gifting experience on Amazon?

“This looks open-ended but it sprawls fast.”

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