Interview experience
Amazon Interview Questions and Answers (2026)
Overview
Section titled “Overview”Amazon’s loop runs an Online Assessment, then a 3-5 round virtual/onsite loop (coding, design, and a mandatory Bar Raiser) - with Leadership Principles questions woven into every single round, not held back for one “behavioural” stage.
Amazon interview process at a glance
Section titled “Amazon interview process at a glance”| Round | Duration | What it tests |
|---|---|---|
| Online Assessment (OA) | ~2-3 hrs total | 2 DSA problems + work-simulation module + LP-aligned behavioural questions |
| Virtual onsite - Coding (1-2 rounds) | 45-60 min each | DSA (medium-hard) + 1-2 Leadership Principle questions |
| Virtual onsite - Design | 45-60 min | OOD for SDE-1 (e.g. parking lot, bookstore); scalable system design for SDE-2+ |
| Bar Raiser | 45-75 min | Deep-dive Leadership Principles only, cross-checked against every other round |
| Hiring manager / offer | 20-30 min | Team fit, location, compensation, close |
Online Assessment (OA)
Section titled “Online Assessment (OA)”Amazon’s OA is longer and more varied than most FAANG assessments: 2 DSA problems (medium-hard, on HackerRank), plus - on most SDE drives - a separate work-simulation module where you react to email/scenario prompts the way an Amazon SDE would, and a set of behavioural MCQs aligned to the Leadership Principles. All test cases on the coding problems typically need to pass to advance; partial credit is less forgiving here than at some other companies.
Common questions
- Maximum sum subarray with at most k elements
- Clone a graph with random pointers
- Merge k sorted lists
- Word ladder / shortest transformation sequence (graph BFS)
- Work-simulation prompts: prioritizing conflicting tasks, responding to a customer escalation email
Full round-by-round breakdowns are on the Amazon interview experience page.
Virtual onsite: coding rounds
Section titled “Virtual onsite: coding rounds”One or two 45-60 minute rounds with live coding, each usually built around a single DSA problem with follow-ups. Interviewers also slip in 1-2 Leadership Principle questions here - Amazon doesn’t wait for a dedicated round to start evaluating LPs.
Common questions
- Longest substring with at most k distinct characters (sliding window)
- Design a data structure supporting insert/delete/getRandom in O(1)
- Maximum path sum in a binary tree
- Find all anagrams in a string
- Design an LRU cache
Virtual onsite: design round
Section titled “Virtual onsite: design round”SDE-1 loops usually ask for object-oriented design (OOD) - classes, relationships, and methods for a system like a parking lot or bookstore - rather than a full distributed-systems design. SDE-2 and above shift toward scalable system design: throughput, storage, and failure handling at Amazon’s scale.
Common questions
- Design a parking lot / bookstore system (OOD, SDE-1)
- Design a URL shortener
- Design a distributed cache or rate limiter
- Design a scalable order-processing or recommendation system (SDE-2+)
The Bar Raiser round
Section titled “The Bar Raiser round”This is Amazon’s most distinctive round, and it isn’t optional: every hire needs sign-off from a Bar Raiser, an interviewer trained specifically to protect the hiring bar and who sits outside your target team. Expect 2-4 Leadership Principle questions pushed far deeper than in earlier rounds - what other options you considered, what data you had, why you chose what you did. The Bar Raiser can see feedback from every other interviewer, so a story you already used in an earlier round is a well-documented way to lose credibility here.
Common questions
- Tell me about a time you went above and beyond for a customer (Customer Obsession)
- Describe a decision you made with incomplete data (Bias for Action)
- Tell me about a time you disagreed with your team’s direction (Have Backbone; Disagree and Commit)
- Give an example where you simplified something that had become too complex (Invent and Simplify)
- Tell me about the highest standard you’ve held yourself or a project to (Insist on the Highest Standards)
Sample STAR frameworks for these - and the rest of the 16 Leadership Principles - are on the Amazon HR interview questions page.
Amazon’s 16 Leadership Principles
Section titled “Amazon’s 16 Leadership Principles”Every Amazon interview, technical or not, is scored against these principles - not just the Bar Raiser round:
Customer Obsession · Ownership · Invent and Simplify · Are Right, A Lot · Learn and Be Curious · Hire and Develop the Best · Insist on the Highest Standards · Think Big · Bias for Action · Frugality · Earn Trust · Dive Deep · Have Backbone; Disagree and Commit · Deliver Results · Strive to be Earth’s Best Employer · Success and Scale Bring Broad Responsibility
Prepare at least one distinct STAR story for each of the principles most relevant to your role, and keep a different story in reserve for the Bar Raiser.
Common technical interview questions and answers
Section titled “Common technical interview questions and answers”Q: How do you design an LRU cache with O(1) get and put?
Combine a hash map with a doubly linked list. The hash map maps a key to the list node holding that key’s value, giving O(1) lookup; the doubly linked list keeps nodes in recency order with the most recently used at the head and the least recently used at the tail. On a get, look the node up and move it to the head. On a put, update the node and move it to the head if the key exists, otherwise create a node at the head and, if the cache is over capacity, remove the tail node and delete its key from the map. The list must be doubly linked so that unlinking a node found via the map is O(1) rather than requiring a scan.
Q: How do you find the longest substring with at most k distinct characters?
Slide a window while keeping a hash map of character counts inside it. Move the right pointer one character at a time and increment its count; while the map holds more than k distinct keys, decrement the count at the left pointer and remove the key when its count hits zero, advancing the left pointer. After each shrink the window is valid, so update the best length. Every character enters and leaves the window at most once, so the time is O(n) and the space is O(k).
Q: How do you build a data structure with insert, delete, and getRandom in O(1)?
Use a dynamic array of values plus a hash map from value to its index in that array. Insert appends to the end of the array and records the index in the map. Delete looks up the index, swaps the last array element into that slot, updates the moved element’s index in the map, pops the last element, and erases the key, which avoids the O(n) shift a naive removal would cost. getRandom simply picks a uniformly random index into the array, which works because the array stays densely packed with no holes.
Q: How do you compute the maximum path sum in a binary tree?
Do a post-order DFS where each call returns the best downward path sum starting at that node and going into at most one child, which is the node’s value plus the larger of its two child returns, clamped at zero so a negative branch is dropped rather than dragged along. Separately, at every node, consider the path that turns at that node, which is node value plus both clamped child contributions, and keep a running global maximum of those. The answer is that global maximum, not the return value of the root call. Time is O(n) since each node is visited once, and space is O(h) for the recursion stack, where h is the tree height.
Q: How do you merge k sorted linked lists?
Push the head node of each of the k lists into a min-heap keyed by node value. Repeatedly pop the smallest node, append it to the output list, and push that node’s next node if it exists. The heap never holds more than k nodes, so with N total nodes the time is O(N log k) and the extra space is O(k). The alternative is divide and conquer, merging lists pairwise in rounds, which reaches the same O(N log k) with O(1) extra space beyond recursion.
Q: How would you solve the word ladder shortest transformation problem?
Treat each word as a graph node with an edge between words differing by exactly one letter, and run a breadth-first search from the start word, since BFS finds the shortest path in an unweighted graph. Put the dictionary in a hash set, and instead of comparing every pair of words, generate neighbours by replacing each position of the current word with each letter and checking set membership, removing visited words from the set so you never revisit. For L-letter words over an alphabet of 26 with N dictionary words, that is roughly O(N times L times 26) time. Bidirectional BFS, expanding from both the start and end words, is the standard optimisation.
Q: How do you find all anagrams of a pattern in a string?
Use a fixed-size sliding window equal to the pattern length with two frequency counts, one for the pattern and one for the current window. Slide the window one character at a time, adding the incoming character’s count and removing the outgoing one, and record the window’s start index whenever the two counts match. Comparing counts each step is O(1) work over a fixed 26-letter alphabet, or track a single matched-character counter to avoid re-comparing, giving O(n) total time and O(1) space.
Q: How would you approach the object-oriented design of a parking lot?
Start by naming the entities and their relationships: a ParkingLot has many Levels, each Level has many ParkingSpots, and a Spot has a size type such as motorcycle, compact, or large. A Vehicle is an abstract base with Car, Bike, and Truck subclasses, each declaring which spot sizes it can occupy, which demonstrates polymorphism. A Ticket links a vehicle to a spot with an entry timestamp, and a separate FeeStrategy interface with hourly or flat implementations keeps pricing swappable without touching the parking logic. Interviewers are scoring encapsulation, sensible responsibility splits, and whether you can extend the design for follow-ups like electric-vehicle charging spots or multiple entry gates.
Frequently asked questions about Amazon interviews
Section titled “Frequently asked questions about Amazon interviews”What is the Amazon interview process?
Amazon’s loop usually runs: 1. Online Assessment (90-120 min core coding + MCQs, with a separate work-simulation module on many drives) - 2 DSA problems plus a scenario-based work-style assessment. 2. Virtual onsite (3-5 rounds, 45-60 min each) - one or two DSA/coding rounds, one OOD/system-design round, and always a Bar Raiser round. Leadership Principles questions are woven into every single round, not just one. Total timeline: 2-6 weeks depending on team and level.
What questions are asked in Amazon interviews?
Coding rounds lean on arrays/strings, sliding window, graphs (BFS/topological sort), linked lists, and caching structures (LRU cache) - medium-to-hard difficulty. Design rounds ask for OOD (e.g. a parking lot or bookstore system) at SDE-1, and scalable system design at SDE-2+. Every round also includes 1-3 Leadership Principle questions, and the Bar Raiser round is almost entirely LP-focused.
What is the Amazon Bar Raiser round?
A mandatory round conducted by a specially trained interviewer from outside your hiring team, whose only job is to protect the hiring bar. It’s built around 2-4 Leadership Principle questions probed in unusual depth - follow-ups on why you chose one option over another, and what the data showed. The Bar Raiser has access to every other interviewer’s feedback and can override a hiring decision, so reusing a story from an earlier round is a well-documented way to lose credibility here.
How many rounds are there in the Amazon interview?
Typically 4-6 touchpoints: the Online Assessment, then a 3-5 round virtual/onsite loop (coding, OOD/system design, and the Bar Raiser), sometimes with a separate recruiter or hiring-manager conversation. SDE-2+ loops usually add a dedicated system-design round; SDE-1 loops lean more on OOD.
How should I prepare for Amazon interviews?
Drill medium DSA patterns (sliding window, graphs, LRU-style caching) until you can explain trade-offs out loud, practice OOD for SDE-1 or scalable system design for SDE-2+, and prepare a fresh STAR story for as many of Amazon’s 16 Leadership Principles as you can - with a different story ready for each round, since the Bar Raiser will notice repeats.