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

Describe Linux and SQL experience

You are being assessed on basic tooling skills as an engineer. Answer: 1. Linux/Unix commands: list commands you are comfortable with and briefly expl...

Software Engineering Fundamentals
6
0
46 people solved
May 28, 2025
Amazon logo
Amazon
Medium
Software Engineer

Explain deep learning and transformer concepts

Deep Learning, Transformers, and Audio ML Concepts You are interviewing for a machine-learning role focused on sequence and audio modeling, such as sp...

Machine Learning
4
0
63 people solved
May 28, 2025
Amazon logo
Amazon
Medium
Product Manager

Answer Amazon PM Behavioral Questions

In an Amazon non-technical Product Manager phone screen, the interviewer asks three behavioral questions, each followed by 2-3 probes for detail. Prep...

Behavioral & Leadership
9
0
63 people solved
Jun 17, 2024
Amazon logo
Amazon
Medium
Product Manager

Evaluate delivery driver performance

You are interviewing for an Amazon non-technical product or operations role. The interviewer asks: How would you evaluate delivery driver performance?...

Product Design & Strategy
5
0
40 people solved
May 7, 2024
Amazon logo
Amazon
Medium
Software Engineer

Add One Source to Minimize Grid Inconvenience

Add One Source to Minimize Grid Inconvenience Implement min_max_inconvenience(grid). grid is a non-empty rectangular matrix containing 0 and 1. A cell...

Coding & Algorithms
2
0
30 people solved
Jul 9, 2026
Amazon logo
Amazon
Easy
Software Engineer

Implement Regular Expression Matching

Implement Regular Expression Matching Determine whether an entire input string matches a pattern containing lowercase letters and two special symbols:...

Coding & Algorithms
1
0
16 people solved
Jul 4, 2026
Amazon logo
Amazon
Easy
Software Engineer

Unify Stock-Trading Profit Variants

Unify Stock-Trading Profit Variants Given daily stock prices, return the maximum profit when you may complete at most max_transactions buy-then-sell t...

Coding & Algorithms
1
0
13 people solved
Jul 4, 2026
Amazon logo
Amazon
Medium
Software Engineer Locked

Leaf Domain Cumulative Scores

This question evaluates a candidate's ability to model hierarchical string data and aggregate values along a tree structure, a common pattern in codin...

Coding & Algorithms
1
0
11 people solved
Jun 23, 2026
Amazon logo
Amazon
Medium
Machine Learning Engineer Locked

Implement Multi-Head Attention from Scratch in NumPy

This coding question tests a machine learning engineer's understanding of Transformer internals by requiring a from-scratch NumPy implementation of mu...

Coding & Algorithms
1
0
4 people solved
Jun 18, 2026
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Amazon
Medium
Software EngineerNew Grad Locked

Caesar Cipher with Translation-Table Optimization

This question tests practical string manipulation and modular arithmetic by requiring implementation of a classic Caesar cipher with correct case-pres...

Coding & Algorithms
2
0
11 people solved
Jun 15, 2026
Amazon logo
Amazon
Medium
Machine Learning EngineerSenior+ Locked

Merge Overlapping Time Ranges

This question evaluates a candidate's ability to work with interval merging, a core array and sorting problem in technical interviews. It tests unders...

Coding & Algorithms
0
0
5 people solved
Jun 14, 2026
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Amazon
Medium
Software EngineerNew Grad Locked

Inventory Allocation by Bid Priority

This question assesses simulation and priority-queue design skills, requiring careful implementation of tiered, round-robin resource allocation under ...

Coding & Algorithms
1
0
13 people solved
Jun 9, 2026
Amazon logo
Amazon
Hard
Software Engineer Locked

Evaluate an Arithmetic Expression in Postfix Notation

Practice a Amazon coding interview problem focused on evaluate an arithmetic expression in postfix notation. The prompt emphasizes edge cases, clean i...

Coding & Algorithms
0
0
4 people solved
Jun 4, 2026
Amazon logo
Amazon
Medium
Machine Learning Engineer Locked

Determine if all courses can be completed

This question evaluates graph-theoretic dependency modeling and cycle-detection competency, measuring the ability to represent course prerequisites as...

Coding & Algorithms
2
0
16 people solved
May 30, 2026
Amazon logo
Amazon
Medium
Software EngineerIntern Locked

Replace Delimited Tokens in a String

This question evaluates string parsing, token recognition, and dictionary lookup competencies for robust text replacement, including handling malforme...

Coding & Algorithms
2
0
15 people solved
May 28, 2026
Amazon logo
Amazon
Medium
Software Engineer Locked

Minimize Circular Redistribution Cost

This question evaluates algorithmic problem-solving skills in array manipulation, circular data structures, load balancing, and cost optimization whil...

Coding & Algorithms
5
0
31 people solved
May 24, 2026
Amazon logo
Amazon
Hard
Software Engineer Locked

Find the Most Common Visit Pattern

This question evaluates the ability to process timestamped event logs and extract ordered length-3 visit sequences, testing skills in sorting, frequen...

Coding & Algorithms
1
0
16 people solved
May 23, 2026
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Amazon
Medium
Software Engineer Locked

Merge Multiple Sorted Arrays

This question evaluates a candidate's competency in array manipulation, merging techniques, and algorithmic complexity analysis, including handling ed...

Coding & Algorithms
1
0
16 people solved
May 22, 2026
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Amazon
Medium
Software Engineer Locked

Maximize Value Under a Budget

This question evaluates combinatorial optimization and algorithm design skills for resource-constrained selection problems, focusing on concepts exemp...

Coding & Algorithms
1
0
12 people solved
May 22, 2026
Amazon logo
Amazon
Hard
Software Engineer Locked

Find a Valid Course Order

This question evaluates graph algorithm skills—specifically topological ordering, directed cycle detection, and analysis of time and space complexity....

Coding & Algorithms
0
0
5 people solved
May 12, 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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