Amazon Interview Questions

Amazon Coding & Algorithms Interview Questions

Practice 695 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.

695 Questions 1 Company08.11.2026
Showing 20 results
Role
Amazon logo
Amazon
Hard
Product Manager

Alexa Domain-Knowledge Data Pipelines

Alexa Domain-Knowledge Data Pipelines: Holidays and Animals Design an end-to-end knowledge pipeline for a global voice assistant such as Alexa to answ...

Product / Decision Making
15
0
59 people solved
Jul 4, 2025
Amazon logo
Amazon
Medium
Product Manager

Behavioral Problem-Solving Scenarios

Behavioral Problem-Solving Scenarios for an Amazon Product Manager Prepare concise, structured examples for an onsite Product Manager behavioral loop....

Behavioral & Leadership
8
0
41 people solved
Jul 4, 2025
Amazon logo
Amazon
Medium
Software Engineer

Detect words formed by multiple dictionary parts

Given an array words of up to 100,000 non-empty lowercase strings (total characters ≤ 1,000, 000), return all strings that can be formed by concatenat...

Coding & Algorithms
3
0
52 people solved
Sep 6, 2025
Amazon logo
Amazon
Medium
Machine Learning Engineer

Explain LLM architecture, tuning, evaluation

LLM Architecture, Positional Embeddings, Fine-Tuning (PEFT), Regularization, and Evaluation Context You are interviewing for a Machine Learning Engine...

Machine Learning
7
0
78 people solved
Sep 6, 2025
Amazon logo
Amazon
Hard
Machine Learning Engineer

Explain a research project in depth

Walk Through a Research Project You Led (End-to-End) Provide a concise, structured narrative that demonstrates scientific rigor, engineering depth, an...

Behavioral & Leadership
7
0
76 people solved
Sep 6, 2025
Amazon logo
Amazon
Medium
Software Engineer

Maintain real-time top-K products from events

Design a data structure/class that ingests a stream of product events and returns the current top‑K products at any time. Events include {timestamp, p...

Coding & Algorithms
3
1
57 people solved
Sep 6, 2025
Amazon logo
Amazon
Medium
Software Engineer

Describe times exceeding and missing expectations

Behavioral Prompt: Exceeding and Falling Below Expectations Context You are interviewing for a Software Engineer role in a technical screen focused on...

Behavioral & Leadership
5
0
43 people solved
Sep 6, 2025
Amazon logo
Amazon
Medium
Software Engineer

Discuss key behavioral experiences

Behavioral Interview (Onsite) — Software Engineer You are preparing for an onsite behavioral and leadership interview. Answer the following prompts us...

Behavioral & Leadership
7
0
69 people solved
Sep 6, 2025
Amazon logo
Amazon
Medium
Software Engineer

Determine string buildability from dictionary

Given a non-empty string s and a list of non-empty words dict, determine whether s can be formed by concatenating words from dict with unlimited reuse...

Coding & Algorithms
3
0
42 people solved
Sep 6, 2025
Amazon logo
Amazon
Medium
Software Engineer

Implement a robust shell CLI

Implement a POSIX-compliant shell script invoked as ./script.sh <username> <path_of_file> that outputs a single line formatted as "<timestamp> <licens...

Coding & Algorithms
4
0
45 people solved
Sep 6, 2025
Amazon logo
Amazon
Medium
Software Engineer

Find longest common contiguous subarray

Given two integer arrays A and B, find the length of the longest contiguous subarray that appears in both arrays. If multiple exist, return any one pa...

Coding & Algorithms
4
0
42 people solved
Sep 6, 2025
Amazon logo
Amazon
Medium
Software Engineer

Check path in N-ary tree

Given the root of an N-ary tree and a sequence of integers path[0..k-1], determine whether there exists a path starting at the root whose node values ...

Coding & Algorithms
2
0
51 people solved
Sep 6, 2025
Amazon logo
Amazon
Hard
Software Engineer

Design a memory usage switcher with thresholds

System Design: In-Process Memory Usage Switcher Context You are designing an in-process memory guardrail for a backend service. The component monitors...

System Design
7
0
55 people solved
Sep 6, 2025
Amazon logo
Amazon
Easy
Software EngineerNew Grad

Implement Interview Coding Problems

Solve the following independent coding tasks from a new-grad software engineering interview. 1. Implement a hash map from scratch. - Support integer k...

Coding & Algorithms
1
0
16 people solved
Nov 22, 2025
Amazon logo
Amazon
Easy
Data Scientist

Find recommended friend pairs by shared listening

Problem (SQL) You work on a music app and want to recommend new friend connections based on listening similarity. Tables Assume the following schemas:...

Data Manipulation (SQL/Python)
10
1
105 people solved
Nov 20, 2025
Amazon logo
Amazon
Medium
Machine Learning Engineer Locked

Design logo infringement detection system

This question evaluates a candidate's competency in ML system design for visual search, covering image representation and embeddings, metric learning,...

ML System Design
2
0
44 people solved
Nov 18, 2025
Amazon logo
Amazon
Medium
Software EngineerSenior+ Locked

Answer Leadership and Collaboration Prompts

This question evaluates leadership, collaboration, interpersonal communication, conflict resolution, adaptability, and self-reflection competencies wi...

Behavioral & Leadership
4
0
37 people solved
Nov 17, 2025
Amazon logo
Amazon
Medium
Software EngineerSenior+ Locked

Solve Shipping and Bundle-Cost Problems

This question evaluates algorithmic reasoning for scheduling and capacity planning (minimum daily shipping capacity) and combinatorial optimization wi...

Coding & Algorithms
2
0
39 people solved
Nov 17, 2025
Amazon logo
Amazon
Medium
Software Engineer

Share examples of impact and simplicity

Share examples of impact and simplicity Behavioral prompt: Exceeding customer expectations and simplifying complex problems Context You are in a softw...

Behavioral & Leadership
5
0
41 people solved
Aug 7, 2025
Amazon logo
Amazon
Medium
Software Engineer

Assess cooldown and plan interview strategy

Assess cooldown and plan interview strategy Interpreting a One-Year Interview Cooldown and Maximizing Signal in a Three-Part Onsite Context You are pr...

Behavioral & Leadership
3
0
41 people solved
Aug 7, 2025

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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