Amazon Interview Questions

Amazon Coding & Algorithms Interview Questions

Practice 689 real Amazon interview questions for 2026. Covers all top categories — Coding & Algorithms, Behavioral & Leadership, Machine Learning, Data Manipulation (SQL/Python), and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Product Manager, and Business Intelligence Engineer roles. Real Amazon interview questions from actual interviews with detailed solutions; use this collection for interview preparation that emphasizes shipping at scale, measurable impact, and the company’s Leadership Principles. Expect coding-heavy assessments for Software Engineer candidates: frequent tree and dynamic-programming problems, two-array optimization patterns, nested object/path lookups, and system-design prompts that mirror product flows (online Minesweeper, pizza-ordering, credit-card and shipping/cost systems), plus leadership and collaboration behavioral prompts. Data Scientist rounds concentrate on experimentation and metrics (A/B design, hand p-values, D7 retention SQL), RAG/recommender evaluation, and product-impact analyses. ML Engineer questions focus on production model design, LLM/agent concepts, reliability (cold start, training stability, online vs offline gaps), and large-scale detection pipelines. PM interviews stress customer-obsessed stories, ambiguity, Alexa product launches, and domain-specific data pipelines. Prepare with timed coding practice, end-to-end experiment writeups, STAR stories framed to Leadership Principles, and mock system-design sessions.

689 Questions 1 Company08.11.2026
Showing 20 results
Role
Amazon logo
Amazon
Medium
Software Engineer

Solve server updates and grid inconvenience minimization

1) You are given an integer array server of length n, where server[i] is the number of requests the i-th server can process. Over multiple days, you r...

Coding & Algorithms
6
0
84 people solved
Sep 6, 2025
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Amazon
Medium
Software EngineerIntern

Describe complex projects, failures, and pivots

In a software engineering internship interview, you may be asked a set of behavioral questions about project complexity, decision-making, failure, and...

Behavioral & Leadership
10
0
150 people solved
Feb 11, 2026
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Amazon
Medium
Product Manager

Amazon Leadership Principles – Behavioral Deep Dive

Amazon Leadership Principles Behavioral Deep Dive Prepare for an Amazon Product Manager Leadership Principles behavioral interview. For each prompt, t...

Behavioral & Leadership
21
0
113 people solved
Jul 4, 2025
Amazon logo
Amazon
Hard
Software Engineer

Design a fraud detection system

Design a Real-Time Payment Fraud Detection System Design an ML-powered system that scores each online card-not-present (CNP) payment during authorizat...

ML System Design
15
0
131 people solved
Aug 10, 2025
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Amazon
Medium
Software EngineerSenior+

Debug distributed-system performance problems

You are asked: “If a distributed system has a performance problem (latency/throughput regression), how would you approach it?” Describe a practical, s...

Software Engineering Fundamentals
5
0
75 people solved
Dec 17, 2025
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Amazon
Hard
Software Engineer

Design a scalable parking lot system

Design a scalable parking lot system System Design: Multi-Level Parking Lot Service Context Design a production-grade parking lot system for a large, ...

System Design
12
0
91 people solved
Jul 16, 2025
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Amazon
Easy
Data Scientist

How would you analyze and test a price increase?

Case Study (Product / Data Science) You work on a subscription-based AI video editing/creation product and leadership is considering raising prices (e...

Analytics & Experimentation
5
0
64 people solved
Nov 20, 2025
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Amazon
Easy
Machine Learning Engineer

Compare decision trees and random forests

Compare decision trees and random forests. In your answer, discuss: - How a single decision tree is built and its main advantages and disadvantages. -...

Machine Learning
7
0
67 people solved
Dec 8, 2025
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Amazon
Hard
Software Engineer

Design an email spam detection system

Design an email spam detection system System Design: End-to-End Email Spam Detection Context Design an end-to-end system that detects and handles spam...

ML System Design
19
0
163 people solved
Aug 10, 2025
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Amazon
Medium
Software Engineer Locked

Find Conflicting Events

This question evaluates algorithmic problem-solving in coding and algorithms, focusing on grouping, sorting, and sliding-window techniques applied to ...

Coding & Algorithms
1
0
9 people solved
Jun 19, 2026
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Amazon
Medium
Software Engineer Locked

Kth Largest Perfect Binary Subtree

This question evaluates a candidate's ability to combine tree traversal with structural validation, requiring recognition of perfect binary subtrees a...

Coding & Algorithms
2
0
8 people solved
Jun 19, 2026
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Amazon
Medium
Machine Learning Engineer Locked

Implement Top-p (Nucleus) Sampling in NumPy

This coding question tests practical implementation of top-p (nucleus) sampling, a core decoding strategy in large language models. It evaluates NumPy...

Coding & Algorithms
0
0
12 people solved
Jun 18, 2026
Amazon logo
Amazon
Hard
Software Engineer

Design an online bookstore for browse and purchase

Design an online bookstore for browse and purchase System Design: Online Bookstore (Browse + Purchase) Context Design an online bookstore that allows ...

System Design
4
0
60 people solved
Jul 31, 2025
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Amazon
Medium
Software Engineer Locked

Build a responsive grid of fixed boxes

This question evaluates front-end layout and responsiveness skills including HTML/CSS and React component rendering, plus performance scaling for larg...

Software Engineering Fundamentals
6
0
69 people solved
Jan 22, 2026
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Amazon
Hard
Software EngineerSenior+

Explain owning and debugging infra modules

Describe a time you were responsible for a storage/distributed-systems/infra component (or a similarly low-level, reliability-critical module). The in...

Behavioral & Leadership
12
0
77 people solved
Jan 22, 2026
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Amazon
Medium
Software Engineer

Find the K-th Smallest Value in Two Sorted Arrays

Find the K-th Smallest Value in Two Sorted Arrays Given two nondecreasing integer arrays and a one-based integer k, return the k-th smallest value in ...

Coding & Algorithms
0
0
3 people solved
Mar 26, 2026
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Amazon
Medium
Software Engineer

Discuss deadlines, feedback, and deep dives

Question This Amazon software engineer behavioral screen walks through a set of leadership-principle prompts. Be ready to tell a distinct, recent stor...

Behavioral & Leadership
8
0
63 people solved
Sep 6, 2025
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Amazon
Medium
Software EngineerNew Grad Locked

Detect and Break a Cycle in a Singly Linked List

This question tests practical knowledge of linked list traversal and pointer manipulation, specifically the ability to detect and resolve cycles using...

Coding & Algorithms
0
0
13 people solved
Jun 15, 2026
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Amazon
Medium
Software EngineerNew Grad Locked

Minimum Bills and Coins to Make Change

This question tests a candidate's grasp of greedy algorithms applied to a classic coin-change problem with fixed denominations. It evaluates practical...

Coding & Algorithms
1
0
11 people solved
Jun 15, 2026
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Amazon
Medium
Software EngineerNew Grad Locked

Minimum Drone Delivery Time on a Ring of Hubs

This question tests a candidate's grasp of circular graph traversal and greedy distance minimization on ring-structured topologies. It evaluates algor...

Coding & Algorithms
0
0
7 people solved
Jun 15, 2026

Frequently Asked Questions

How difficult are Amazon interview questions for software, data, and product roles?
Amazon interviews are competitive and deliberately broad: expect medium-to-hard algorithmic coding for software roles, deep design thinking for system and architecture questions, rigorous experiment and metrics work for data roles, and leadership-driven behavioral prompts for product and PM positions. Difficulty scales with level; early-career loops focus on correctness and problem patterns, senior loops demand scalable design, tradeoff justification, and measurable impact. The Bar Raiser raises the bar on long-term ownership and cultural fit. Overall, the process weeds for both technical depth and the ability to explain tradeoffs, so prepare to demonstrate repeatable problem solving under time pressure.
What is the Amazon interview process and where do the top categories and positions appear in the loop?
Amazon typically uses a staged process: resume screen, role-specific assessments or phone screens in some tracks, then the onsite loop of 4–6 interviews including a Bar Raiser. Coding and algorithms rounds dominate for Software Engineer interviews, while system design appears in one or more senior technical rounds. Data Scientist interviews blend SQL/Python casework, A/B test design, and inferential questions. Machine Learning Engineer loops probe model deployment, offline to online debugging, and NLP/agent design. Product and BI roles focus on metrics, product tradeoffs, and Leadership Principles throughout the loop, with role-specific deep dives tied to the job description.
How long should I prepare for Amazon interviews and what should a timeline look like?
Aim for a focused 6–12 week plan for experienced roles and 4–8 weeks for early-career candidates. Weeks 1–3: shore up fundamentals — arrays, trees, graphs, DP, and core SQL windowing. Weeks 4–6: simulate timed coding rounds, practice system design high-level tradeoffs, and build STAR stories mapped to Leadership Principles. Weeks 7–10: run mock loops with behavioral pressure, refine experiment and ML case studies, and rehearse tradeoff conversations. Leave final 1–2 weeks for targeted practice on role-specific themes such as shipping costs, RAG evaluation, or Alexa product scenarios.
Which key subtopics should I master to perform well across Amazon's top roles?
Master algorithmic patterns including trees, dynamic programming, two-pointer and graph traversals, and complexity justification for coding rounds. For system design, focus on APIs, data models, scaling, caching, reliability, and monitoring. Data roles require SQL window functions, cohort and retention analysis, A/B test design and power, and RAG/evaluation methods for ML-backed features. Machine learning engineers must know model stability, cold-start strategies, online-offline mismatch debugging, and agent alignment basics. Product candidates should be fluent in metric design, customer-observed data pipelines, and prioritization with quantifiable impact.
What standout tips and common pitfalls should I know before interviewing at Amazon?
Start every behavioral or technical story with context and measurable outcomes; interviewers care about specific impact and tradeoffs. Use STAR for leadership prompts but emphasize metrics and follow-on changes. In coding, verbalize assumptions, test edge cases, and discuss complexity and alternative approaches. In design rounds, ask clarifying questions, scope deliberately, and justify scaling choices. Common pitfalls include weak quantification of impact, ignoring the Leadership Principles, failing to probe requirements, and delivering designs without operational considerations. Practice mock loops and incorporate Bar Raiser-style feedback to close gaps before the real loop.

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