Amazon Interview Questions (2026)
2947 questions · 1661 experiences · 13 discussions · LeetCode (3345) · 1p3a_oj (736) · Reddit (256) · GeeksforGeeks (141) · 1p3a (106) · InterviewDB (31) · Blind (6)
Browse by role
Top topics
4,456 more Amazon reports behind the paywall
One payment, permanent access to this company. No subscription, nothing to cancel.
4621 entries
amazon sde summer intern 2026 onsite interview experience
amazon sde2 online assessment: algorithm and ai debug challenges
2026 amazon robotics sde intern tech phone screen experience
Amazon SDE2 Interview Experience Technical and Behavioral Deep Dive
Amazon SDE-2 LLD Round Rule Engine Design
Amazon SDE2 Interview Experience February 2026 Offer Received
Amazon SDE II Online Assessment Coding Questions
AWS coding interview from last year; Claude can't solve
My Amazon SDE-1 interview Experience - Rejected after Bar Raiser
Amazon SDE 1 Interview Experience 2026 with DSA and Gen AI Rounds
Amazon SDE Intern VO Interview Experience: Morse Code and Word Break II
Amazon and TCS 2026 Online Assessment Logic and DSA Guide
Amazon Intern Online Assessment Coding Problems and Approaches
Amazon SDE-1 India (AUTA) Interview Experience
Amazon SDE Intern Interview Experience and OA Review
Amazon Online Assessment OA Coding Question Binary String Reversal
Amazon SDE 2 Interview Experience DSA LLD and HLD
Anyone who recently gave Amazon Technical Interview? Please share questions (3-4 months)
Amazon SDE Interview Questions That Keep Coming Back (Oct-Dec 2025)
[repost] , Need Help for Amazon OA SDE1.
Amazon SDE-2 Onsite Interview Recent DSA LeetCode Topics Overview
2025 Amazon and Google OA Stock Strategy Sliding Window Interview Prep
Adding this question to an Online Assessment is criminal .
Amazon Low Level Design Interview Questions
Amazon SDE 3 Onsite Data Structures and Algorithms Interview Experience
amazon sde summer intern 2026 onsite interview experience
Question Details
First in-person interview I have ever done
It wasn't bad, I thought because of Amazon's hiring spree and invitation to on-site interview, the hiring criteria requirement would be lax, but it wasn't.
Here was the interview process and experience:
Interview process
2, 60-minute interviews back to back
(45 minutes technical, 15 minutes behavioral/resume grill/AI questioning)
First interview
15 minutes:
Talking about resume, projects I've done, previous internship experience.
45 minutes:
Similar to system design kind of question, given multiple data structures, must augment the maps to extract certain features, get the elements that fulfill a certain criteria, etc. Wasn't Leetcode style, but wasn't a system design either. Almost like generic coding ability.
Second interview
45 minutes:
Question similar to encode and decode strings. Given a string, objective is to replace all instances of ":x:" with "y". every key value would start with ";" and end with ":", which he had explicitly stated. Using this, my original solution was an iterative approach, where upon encountering a ";", I checked all possible keys and would see if the actual end of the key I'm checking matched. if it did, then replace and move on. had some issues with the string replacement as I was using a little bit more memory, didn't know the solution to getting optimal space (instead of using strings, make it an array and then use .join). I had an almost optimal solution but was really nervous and overcomplicated it. We walked through the problem, and I felt very nice talking to him and had a very positive experience (thought I did good in that), but apparently not.
15 minutes:
Asking about typical behavioral questions, talked a little bit about how I use AI to code. Also talked about C/C++ since I just finished a course in that. It was super nice since he also used C/C++ and asked me questions about what tools I use to debug (not AI) — valgrind, GDB, etc.
AI-heavy questions.
Overall, the experience was not bad. It's just that I guess I didn't meet the bar. Very disappointed.
Topics
More from Amazon
Related companies
Amazon Interview Process Overview
The Amazon interview process typically includes a recruiter screen, one to two technical phone screens, and a 4-6 round on-site or virtual on-site loop. Each round serves a distinct calibration purpose: coding rounds measure correctness, code quality, and complexity reasoning; system design rounds measure architectural judgment at the appropriate level; behavioral rounds measure ownership, leadership scope, and collaboration. Reports tagged on LeakCode from 2024-2026 show Amazon runs a calibrated process consistent with industry norms for companies of its tier.
Difficulty calibration: Amazon coding rounds typically run medium difficulty with follow-up depth as the senior discriminator. System design rounds expect production-grade trade-off articulation at L4+ levels. Behavioral rounds expect quantified outcomes ("reduced p99 latency from 800ms to 120ms") rather than vague impact claims. The candidates who advance consistently demonstrate clear thinking out loud rather than perfect final answers.
How To Use Amazon Question Reports
Real candidate-reported interview questions are a calibration tool, not a memorization target. Amazon updates its question pool every 2-4 months; memorizing exact problems risks misleading you when the interviewer uses a variant. The high-leverage approach: identify the patterns that appear repeatedly in Amazon reports, practice those patterns on similar (not identical) problems, and use the reports to understand the interviewer's typical follow-up depth.
Filter the questions above by round type, difficulty, and recency. Focus first on reports from the past 6-12 months; older reports may reference questions that have since rotated out of Amazon's pool. Reports tagged with quantified difficulty and explicit round type are higher-signal than reports without those tags. The metadata filters help you build a focused study plan in 1-2 hours rather than 8-10 hours of unstructured browsing.
Common Amazon Interview Mistakes
Reports tagged "no hire" at Amazon consistently surface a few patterns: jumping into code without clarifying requirements, coding silently for extended periods, missing edge cases (empty input, single element, large input, overflow), producing working code the candidate cannot refactor when probed, and behavioral stories that use "we" instead of "I" diluting individual signal. Strong candidates explicitly avoid these patterns by following a consistent round template.
The single most predictive failure mode in recent reports: not asking clarifying questions. Interviewers are explicitly trained to weight this dimension. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into implementation immediately. Strong candidates also verbalize their approach before writing code; weak candidates code in silence and lose the communication dimension of the round's calibration.
More Amazon question views