Company
Amazon interview questions
653 practice questions in the style of Amazon's interviews, covering Behavioral & Leadership, System Design, Coding & Algorithms, Product / Decision Making, Data Manipulation (SQL/Python), Analytics & Experimentation, Statistics & Math, Software Engineering Fundamentals, Machine Learning, ML System Design, Product Design & Strategy.
50 easy471 medium132 hard
Amazon interview questions by the numbers
Last updated
Katkat has 653 Amazon interview questions. The largest topics are Coding & Algorithms (35%), Behavioral & Leadership (26%) and System Design (9%). By difficulty: 8% easy, 72% medium and 20% hard. The most common round is Technical Screen (49%). Frequent concepts include System Design, Behavioral, Leadership and Algorithms.
Topics
- Coding & Algorithms35% · 226
- Behavioral & Leadership26% · 168
- System Design9% · 56
- Machine Learning8% · 55
- Analytics & Experimentation4% · 28
- ML System Design2% · 16
Difficulty
- Easy8% · 50
- Medium72% · 471
- Hard20% · 132
Interview rounds
- Technical Screen49% · 318
- Onsite37% · 243
- Online Assessment11% · 71
- Other2% · 13
- HR Screen1% · 8
Roles
- Software Engineer61% · 400
- Data Scientist22% · 144
- Applied Scientist8% · 54
- Product Manager3% · 22
- Business Intelligence Engineer2% · 13
Frequent concepts
- System Design5% · 34
- Behavioral5% · 32
- Leadership4% · 29
- Algorithms4% · 23
- Distributed Systems4% · 23
- Optimization3% · 21
Most mentioned in interview experiences
- 1.Answer Amazon Leadership Principles questions44 reports
- 2.Answer common Amazon behavioral questions17 reports
- 3.Answer Amazon Behavioral Questions15 reports
- 4.Answer Leadership and GenAI Behavioral Questions15 reports
- 5.Solve Algorithmic Challenges in Online Coding Assessments15 reports
- 6.Assess Candidate's Alignment with Amazon Leadership Principles13 reports
- 7.Solve LeetCode string and list problems11 reports
- 8.Answer common leadership prompts10 reports
- 9.Demonstrate Leadership Principles in Projects9 reports
- 10.Amazon Leadership Principles – Behavioral Deep Dive8 reports
Counted from 213 candidate interview experiences on Katkat. How we collect and count
Showing 211–240 of 653 results
Design a TTL-aware LRU cache with synchronized access, capacity eviction, and expiration heaps or timing wheels instead of full-table scans.
AmazonSoftware EngineerSoftware Engineering FundamentalsOnline AssessmentThis problem tests your ability to design a distributed system component that maintains cluster balance by dynamically splitting and merging data shards based on size thresholds.
AmazonSoftware EngineerSoftware Engineering FundamentalsOnsiteAn object-oriented design and coding exercise for a train line where each segment between adjacent stations costs one unit. It asks for a fare function between two stations, a route class that loads route data and supports adding stations at runtime, and a weekend rule that caps the total fare.
AmazonSoftware EngineerSoftware Engineering FundamentalsOnsiteThis question evaluates competency in system design and distributed systems architecture, including API design, scalable short-code generation, data modeling and storage/sharding, caching and CDN strategies, consistency and fault-tolerance trade-offs, rate limiting and abuse prevention, analytics, compliance, and capacity planning.
AmazonSoftware EngineerSystem DesignOnsiteThis problem tests object-oriented modeling and state management by requiring the design of a class structure that handles credit limits, transaction authorization, and balance tracking.
AmazonSoftware EngineerSoftware Engineering FundamentalsTechnical ScreenThis question tests the ability to architect a distributed database write path that decouples compute from storage, specifically focusing on how to maintain ACID properties during failures.
AmazonSoftware EngineerSystem DesignTechnical ScreenThis problem evaluates your ability to design a multimodal agent capable of interpreting UI elements and executing sequences of actions to complete user-defined tasks on a computer screen.
AmazonApplied ScientistML System DesignOnsiteThis question evaluates skills in designing a distributed configuration and subscription service, covering API design, real-time notification semantics (delivery and ordering guarantees), versioning, concurrency and thread-safety, durability and recovery, multi-tenant isolation, security, and scalability concerns.
AmazonSoftware EngineerSystem DesignOnsiteThis question tests the ability to design a distributed, fault-tolerant system capable of scheduling and executing tasks at a massive scale with strict latency requirements.
AmazonSoftware EngineerSystem DesignOnsiteThis question evaluates object-oriented and API design skills, filesystem semantics (pattern matching, file types, timestamps, permissions, symlink handling), traversal and concurrency strategies, and robustness for large or error-prone directory trees.
AmazonSoftware EngineerSystem DesignOnsiteThis question evaluates understanding of fixed-capacity circular queue data structures, array-based indexing, modular arithmetic, and the requirement for constant-time (O(1)) enqueue/dequeue operations.
AmazonSoftware EngineerCoding & AlgorithmsOnsiteThis problem evaluates your ability to design a scalable, low-latency fraud detection system for an e-commerce platform, focusing on handling class imbalance, feature engineering, and the challenges of delayed feedback loops.
AmazonSoftware EngineerML System DesignTechnical ScreenThis interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Design a hierarchical locking tree states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
AmazonSoftware EngineerCoding & AlgorithmsTechnical ScreenAn Amazon software-engineer system-design screen: design a system that captures keyboard and mouse events and reconstructs exactly what the user typed. It tests low-latency event capture, total ordering across multiple devices, IME/composition and grapheme-safe text reconstruction, mouse selection and clipboard/undo-redo, plus durable persistence with deterministic crash-safe replay.
AmazonSoftware EngineerSystem DesignTechnical ScreenThis question tests your ability to design a high-throughput data ingestion pipeline and storage architecture for a fleet of IoT sensors, focusing on write-heavy scalability and time-series query performance.
AmazonSoftware EngineerSystem DesignTechnical ScreenAn Amazon software engineer system design question: design a log filtering and analytics service that ingests high-volume application logs and supports attribute/substring filtering, error counts over a time window, and hourly histograms by pattern or ID. It tests ingestion API design, dual search + OLAP storage with hourly rollups, schema and indexing, late/duplicate-event handling, partitioning and retention, and correctness-vs-latency trade-offs with complexity analysis.
AmazonSoftware EngineerSystem DesignTechnical ScreenThis question evaluates system design and operational engineering skills in process memory management, runtime configurability, observability, and reliability, and belongs to the System Design domain; it primarily tests practical application with system-level conceptual reasoning.
AmazonSoftware EngineerSystem DesignTechnical ScreenThis question tests your ability to design a scalable, distributed reservation system that handles resource allocation (bin packing) under concurrency constraints.
AmazonSoftware EngineerSystem DesignOnsiteDesign a no-repeat frequency-based music player with addUserSongs and getNextSong APIs. Covers max-heap data structures, lazy deletion, cycle resets, mid-cycle song additions, and complexity.
AmazonSoftware EngineerCoding & AlgorithmsOnsiteThis question tests your ability to design a system that manages complex dependency graphs, ensuring package integrity, version compatibility, and atomic installation operations.
AmazonSoftware EngineerSystem DesignTechnical ScreenThis question evaluates object-oriented design and software architecture skills, focusing on class modeling, responsibilities, relationships, state management, pricing, payment flows, and extensibility.
AmazonSoftware EngineerSoftware Engineering FundamentalsTechnical ScreenThis question tests the ability to design an end-to-end, scalable time-series forecasting pipeline, focusing on anomaly handling, structural decomposition, uncertainty quantification, and model validation strategies.
AmazonData ScientistMachine LearningTechnical ScreenThis question tests your ability to design a distributed system architecture capable of handling high-volume image uploads, metadata storage, and low-latency feed retrieval.
AmazonSoftware EngineerSystem DesignOnsiteDesign a scalable parking lot system evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
AmazonSoftware EngineerSystem DesignTechnical ScreenThis problem tests your ability to implement efficient weighted random selection using prefix sums and binary search, and handling state updates.
AmazonSoftware EngineerCoding & AlgorithmsTechnical ScreenAmazon data scientist experimentation prompt on designing an A/B test for an energy-usage dashboard redesign, including hypotheses, metrics, guardrails, power, test duration, seasonality, and analysis methods.
AmazonData ScientistAnalytics & ExperimentationOnsiteDesign a service where an AI agent investigates flagged payment events inside a stream running at roughly 1 TB of events per day, covering capacity math, where the agent sits relative to deterministic detection, and the cost and adversarial-input guardrails that keep it from becoming a liability.
AmazonSoftware EngineerSystem DesignTechnical ScreenTests object-oriented design and state-machine modeling for a self-service package locker station, focusing on parcel allocation, code expiration, and physical-vs-logical state consistency.
AmazonSoftware EngineerSystem DesignTechnical ScreenDesign an Automated Home-Price Valuation Model evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
AmazonData ScientistMachine LearningTechnical ScreenDesign an extensible cinema pricing engine with validated money and multiplier types, composable policies, explicit calculation and rounding, compatibility checks, versioned configuration, itemized quotes, and boundary tests.
AmazonSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
Amazon interview experiences
All 396 →- L6 Phone Screen With an Impatient Interviewer, LCA Follow-up StuckAmazon · Software Engineer · Senior+ · Technical Screen · Oct 2026
The interviewer was impossible to find anywhere online, I couldn't find a thing about him and I'm speechless. BQ: 1. How do you evaluate customer experience? 2. A major unexpected obstacle. For the first one, I think the point of the question was the evaluation part, and my story was just directly collecting feedback, which he wasn't happy with 😭 For the second one, he felt the obstacle wasn't ma…
- Three Rounds of Graphs, System Design and Leadership PrinciplesAmazon · Software Engineer · Technical Screen · Oct 2026
I interviewed with the Agentic AI security product team under AWS. The location is Austin. Every round was 1 hour. Round 1 was a DAG topological sort. It was pretty good, pretty basic. Round 2 was another directed graph problem. This team really likes graph problems. It was something like working out what you need to make a cake, and it is very similar to a LeetCode problem. Round 3 was a traditi…
- Four Rounds with Detailed Behavioral QuestionsAmazon · Software Engineer · Onsite · Sep 2026
The author describes four Amazon virtual-onsite interviews for an SDE2 role, each combining behavioral discussion with technical work. The technical topics were dependency ordering and selective reruns, a high-volume inventory-update service, an extensible document-search library, and merging timestamp-ordered event streams without loading everything into memory. Behavioral questions examined inv…
- One DSA Round, Two Mediums, RejectedAmazon · Frontend Engineer · Technical Screen · Sep 2026Rejected
I applied through a LinkedIn post for SDE I (Frontend). HR contacted me over a call and we discussed the further rounds. Round 1 (PS-DS Round) (1hr) Two DSA medium questions were asked, and I was able to solve both of them within the time limit (~40 mins). The interviewer was helpful and provided hints. Q1. Lowest Common Ancestor of a Binary Search Tree Q2. Ones and Zeroes Explain brute force, th…
- One Virtual Onsite Round with BQ Drill-downs and a Checkout Price Engine OODAmazon · Software Engineer · Onsite · Sep 2026
Three BQ questions: Q1: Can you tell me about a time when you pushed back against a decision that negatively impacted your team? What was the issue? How did it turn out? Q2: Can you tell me about a time when a system was failing intermittently, and the very obvious metrics were all looking good? How did you find the root cause, and how long did it take? Q3: Can you tell me about a problem you had…
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