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 EngineerSenior+

Discuss Challenges, Difficult Colleagues, and Multitasking

Discuss Challenges, Difficult Colleagues, and Multitasking Prepare responses to three behavioral questions. Use real examples, keep context concise, a...

Behavioral & Leadership
6
0
48 people solved
Jul 17, 2026
Amazon logo
Amazon
Easy
Software EngineerIntern

Find the Lowest Common Ancestor in a Binary Tree

Find the Lowest Common Ancestor in a Binary Tree Problem Implement lowestCommonAncestor(left, right, root, first, second) -> nodeId. The binary tree h...

Coding & Algorithms
1
0
12 people solved
Aug 1, 2026
Amazon logo
Amazon
Easy
Software EngineerIntern

Compute the Minimum Number of Meeting Rooms

Compute the Minimum Number of Meeting Rooms Problem Implement minimumMeetingRooms(intervals) -> roomCount. Each meeting is a half-open interval [start...

Coding & Algorithms
0
0
11 people solved
Aug 1, 2026
Amazon logo
Amazon
Hard
Software Engineer

Minimize Replacements So Equal Product Values Are Contiguous

Minimize Replacements So Equal Product Values Are Contiguous You are given the quality value of each product in a line. In one operation, choose two d...

Coding & Algorithms
13
1
160 people solved
Jul 12, 2026
Amazon logo
Amazon
Medium
Software Engineer

Resolve Package Dependencies with Cycle Detection

Implement buildOrder(dependencies, target), which returns the packages needed to build and install target in a valid dependency-first order. dependenc...

Coding & Algorithms
1
0
12 people solved
Jul 29, 2026
Amazon logo
Amazon
Hard
Software EngineerSenior+

Explain BIOS and UEFI Firmware Mechanisms

Explain BIOS and UEFI Firmware Mechanisms Answer the following firmware and low-level systems questions. State assumptions about architecture and firm...

Software Engineering Fundamentals
4
0
50 people solved
Jul 15, 2026
Amazon logo
Amazon
Easy
Software EngineerIntern

Determine Whether One Person Can Attend Every Meeting

Determine Whether One Person Can Attend Every Meeting Problem Implement canAttendAllMeetings(intervals) -> canAttend. Each meeting is a half-open inte...

Coding & Algorithms
1
0
9 people solved
Aug 1, 2026
Amazon logo
Amazon
Medium
Machine Learning Engineer

Implement Stable Sigmoid, Softmax, and Scaled Dot-Product Attention

Implement Stable Sigmoid, Softmax, and Scaled Dot-Product Attention Implement the mathematical core of three common neural-network operations without ...

Machine Learning
4
0
56 people solved
Jul 2, 2026
Amazon logo
Amazon
Medium
Software Engineer

Track the Contiguous Package Frontier and Missing IDs

Track the Contiguous Package Frontier and Missing IDs Design a PackageTracker for non-negative package IDs that are expected to begin at 0 but may arr...

Coding & Algorithms
1
0
10 people solved
Jul 27, 2026
Amazon logo
Amazon
Medium
Software Engineer

Architect an AI Chatbot for Enterprise Users

Architect an AI chatbot for enterprise users over internal knowledge and tools. `hint Hint 1 Start by stating assumptions, then work from requirements...

System Design
15
0
141 people solved
Jul 1, 2026
Amazon logo
Amazon
Easy
Software Engineer

Design a Scalable News Feed

Design a Scalable News Feed Scenario Design the home-feed system for a social product. Users publish posts, follow other accounts, and request a pagin...

System Design
2
0
30 people solved
Jun 22, 2026
Amazon logo
Amazon
Hard
Machine Learning EngineerNew Grad

Explain Core ML Interview Concepts

You are in a phone screen for an applied scientist / machine-learning engineer role and are asked to verbally explain a set of machine-learning fundam...

Machine Learning
236
0
1931 people solved
Apr 27, 2026
Amazon logo
Amazon
Medium
Software EngineerSenior+

Implement Multi-Player Tic-Tac-Toe

Implement Multi-Player Tic-Tac-Toe Implement a game class for an N by N board and K players. Each player has a distinct one-character printable mark. ...

Coding & Algorithms
4
0
50 people solved
Jul 17, 2026
Amazon logo
Amazon
Medium
Data Scientist Locked

Reserving an Elevator for Food Deliveries

This question tests a data scientist's ability to design a rigorous A/B experiment for a real-world operational policy with competing stakeholder outc...

Analytics & Experimentation
19
0
289 people solved
Jun 8, 2026
Amazon logo
Amazon
Hard
Software Engineer AI

Circular Drone Hub Delivery Route

A drone delivery network is laid out as a ring of n hubs, numbered 0, 1, ..., n - 1. Each hub is connected by a direct air corridor to its two neighbo...

Coding & Algorithms
5
0
60 people solved
Jun 28, 2026
Amazon logo
Amazon
Hard
Software EngineerSenior+

Resolve a Technical Disagreement with a Teammate

Resolve a Technical Disagreement with a Teammate Prompt Tell me about a meaningful technical disagreement with a teammate. Explain what was at stake, ...

Behavioral & Leadership
3
0
61 people solved
Jul 5, 2026
Amazon logo
Amazon
Medium
Frontend Engineer

Implement an Accessible Autocomplete Search Component

Implement an Accessible Autocomplete Search Component Build a frontend autocomplete search bar from a supplied visual design. As the user enters text,...

Software Engineering Fundamentals
3
0
31 people solved
Jul 7, 2026
Amazon logo
Amazon
Medium
Software EngineerSenior+ Locked

Design a Distributed Cron Job Scheduler

Design a distributed cron scheduler that creates recurring runs, dispatches work, tracks attempts, and recovers from crashes and partitions. Address d...

System Design
3
0
54 people solved
May 29, 2026
Amazon logo
Amazon
Easy
Software Engineer

Describe Work Beyond Your Formal Responsibilities

Describe Work Beyond Your Formal Responsibilities Tell me about a time you took on useful work outside the normal boundaries of your role. Why did the...

Behavioral & Leadership
5
0
42 people solved
Jul 7, 2026
Amazon logo
Amazon
Medium
Software Engineer Locked

Object-Oriented Design: Snake Game

This question evaluates a candidate's ability to translate a familiar game into a clean object-oriented model, covering class decomposition, encapsula...

System Design
9
0
145 people solved
Jun 19, 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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