Amazon Interview Questions 2026: Leadership Principles

SDE-1 (0–3 years experience): 1. Online Assessment (90–120 min): 2 coding problems (LeetCode Medium) + 1–2 LP-style written questions 2. Phone Screen (45 min): 1 coding problem + 1–2 LP questions 3. Virtual Loop (5–6 rounds, each 45–60 min): - Round 1: Coding + LP (2 coding problems, 2 LP questions) - Round 2: Coding + LP (2 coding problems, 2 LP questions) - Round 3: System Design (basic, for SDE-1) + LP - Round 4: Bar Raiser (most rigorous round: harder coding + deeper LP probing) - Round 5: Hiring Manager (LP-focused, role alignment)

SDE-2 (3–7 years experience): Same structure, but: - Coding: LeetCode Medium-Hard expected - System Design: full system design round (1 hour, design a production system) - LPs probed with larger-scope examples - Bar Raiser is the most challenging round and always involves someone outside the hiring team

What is the Bar Raiser? Every Amazon hiring loop includes a Bar Raiser: a trained Amazon employee (from any team) whose job is to ensure Amazon only hires people who raise the average bar. The Bar Raiser has the power to veto any hire, regardless of the hiring team's preference. Bar Raiser rounds are typically the hardest: expect the toughest LP questions ('Tell me about a time you made a decision with incomplete data that turned out to be wrong') and the hardest coding problem.

Amazon has 16 Leadership Principles. Every LP can appear in an interview question. Here are the 8 most commonly tested in Indian hiring loops:

1. Customer Obsession 'Tell me about a time you put the customer's needs above what was technically easiest.' Prep: Think about a time you changed a technical decision because of its impact on users: even when it meant more work for you.

2. Ownership 'Tell me about a time you took ownership of a problem that wasn't technically yours to fix.' Prep: A story where you identified a problem outside your direct scope and fixed it without being asked.

3. Invent and Simplify 'Tell me about a time you found a simpler solution to a complex problem.' Prep: A story where you reduced complexity: fewer steps, fewer dependencies, less code, a simpler process.

4. Are Right, A Lot 'Tell me about a time you made a call when others disagreed with you, and you were right.' Prep: Technical or product decision where you disagreed with the group, pushed your position with data, and the outcome validated your reasoning.

5. Dive Deep 'Tell me about a time you had to dig deep into data or code to find the root cause of a problem.' Prep: A debugging or investigation story: the more specific about the steps you took, the better.

6. Bias for Action 'Tell me about a time you took action before having all the information.' Prep: A story where you made a calculated decision under time pressure without waiting for complete data, and the outcome was reasonable.

7. Deliver Results 'Tell me about a time you delivered a project despite significant obstacles.' Prep: A story with a specific deliverable, a specific obstacle, and a specific measurable outcome.

8. Earn Trust 'Tell me about a time you received critical feedback. How did you respond?' Prep: A story where you received genuine critical feedback, didn't become defensive, and changed your behaviour or output in response.

Format for LP answers: the STAR-LP hybrid: Amazon explicitly uses STAR, but with extra emphasis on the Result AND on what you personally learned or changed. Every LP answer should end with: 'What I took from this...' or 'Since then, I now...'

Difficulty expected at Amazon India: - SDE-1: LeetCode Medium (must solve in 20–25 minutes), occasionally Hard - SDE-2: LeetCode Medium-Hard (must solve optimally), Hard expected - Online Assessment: Medium (90 min for 2 problems: should clear both test cases)

Most-asked DSA topics at Amazon India:

1. Arrays and Strings (most common) - Two pointers - Sliding window - Kadane's algorithm (maximum subarray) - Prefix sums

2. Trees and Graphs - Binary tree traversals (level-order BFS is especially common) - Lowest Common Ancestor - Graph BFS/DFS - Number of islands (connected components)

3. Dynamic Programming - Knapsack variants - Longest Common Subsequence/Substring - Edit distance - Coin change

4. Design patterns in DS problems - Stack for monotone stack problems - Heap (priority queue) for top-K problems - HashMap for frequency/lookup problems

Sample problem (SDE-1 level): 'Given an array of integers, find the maximum product subarray.' ```python def max_product(nums): max_p = min_p = result = nums[0] for n in nums[1:]: candidates = (n, max_p * n, min_p * n) max_p, min_p = max(candidates), min(candidates) result = max(result, max_p) return result ```

Interview communication at Amazon: Amazon interviewers explicitly want you to: 1. Clarify the problem before coding (ask about edge cases, constraints) 2. State your approach and complexity before writing code ('I'm going to use a sliding window, O(n) time, O(1) space') 3. Walk through your code with a test case after writing it 4. Handle edge cases explicitly ('If the array is empty, I'd return 0') Silent coding: writing code without narrating: is a red flag at Amazon regardless of whether the code is correct.

Amazon's system design round has a distinctive framing: the interviewer often asks you to design a system that Amazon has actually built. Common prompts:

• 'Design Amazon's product recommendation system'
• 'Design a notification system for order status updates to 500M customers'
• 'Design Amazon's product search'
• 'Design a distributed rate limiter for AWS API Gateway'
• 'Design a cart system that handles flash sale spikes'

Amazon-specific design considerations to demonstrate:

Scale: Amazon operates at massive scale. Always design for 100M+ users unless told otherwise. Show you think about: write-heavy vs read-heavy patterns, partitioning strategies, global vs regional deployment.

Durability: Amazon's systems cannot lose data. Always ask: 'What are the durability requirements?' Demonstrate knowledge of: replication factor, write-ahead logs, exactly-once delivery semantics.

Availability over consistency: Amazon's Dynamo paper (basis of DynamoDB) explicitly chose availability and partition tolerance (AP) over consistency. When appropriate, propose AP systems and explain the tradeoff.

Cost efficiency: Unlike Google or Facebook, Amazon as a business is deeply cost-conscious. Mentioning cost tradeoffs (S3 Glacier for cold storage vs EBS for hot data, spot instances for batch jobs) signals you understand Amazon's culture.

Sample strong answer opening for 'Design an order notification system': 'Before I start designing, let me clarify: are we talking about push notifications (mobile app), SMS, email, or all three? How many orders per day: are we designing for Amazon's global scale of 10M+ orders/day? And what's the latency requirement: does a customer need to receive the notification within 1 second, or is 30 seconds acceptable for non-payment notifications? [...After clarification...] Given 10M orders/day = ~120 orders/second average, with up to 3 notification events per order, we need to handle ~360 events/second. I'd design this as an event-driven system with an order event bus as the backbone...'

SDE-1 (0–3 years): - Base: ₹18–32 LPA - Stock (RSUs): ₹8–20 LPA vested over 4 years (back-weighted: 5%/15%/40%/40%) - Signing bonus: ₹2–5 LPA (Year 1 only, to offset stock vesting cliff) - Total Year 1 compensation: ₹28–52 LPA - Total Year 2-4 compensation (with stock vesting): ₹30–60 LPA

SDE-2 (3–7 years): - Base: ₹28–48 LPA - Stock (RSUs): ₹20–45 LPA vested over 4 years - Total Year 1: ₹45–80 LPA

SDE-3 / Principal SDE: - Total compensation: ₹80–150+ LPA (heavily stock-weighted)

Important nuances about Amazon India compensation:

1. Base salary cap: Amazon India caps base salaries lower than pure product companies like Google because Amazon compensates heavily via stock. The base salary alone looks lower than Flipkart or Swiggy at the same level.

1. RSU back-loading: Amazon's stock vesting schedule (5%-15%-40%-40%) means Year 1 and 2 compensation is significantly lower than Year 3 and 4. Candidates who leave after 2 years give up 80% of their stock.

1. Amazon vs Google India comparison: Google India base salaries are higher; Amazon India stock packages are often larger for senior roles. Total comp at SDE-2 level is broadly comparable.

1. Role-adjusted pay: Amazon India has separate salary bands for teams: Alexa India, Amazon Pay India, AWS India, Amazon Retail India. AWS roles typically pay 10–20% above retail Amazon roles at equivalent levels.