FAANG

Amazon

Free first round · 20 min · no credit card

16 Leadership Principles, Bar Raiser-led. Customer Obsession is non-negotiable.

Interview philosophy

How Amazon actually interviews

Amazon's interview process is the most behaviorally-weighted of the FAANG. Each interviewer is assigned 2-3 of Amazon's 16 Leadership Principles to probe, and roughly half of every onsite round is dedicated to LP-driven behavioral questions. Candidates who under-prepare LPs and over- prepare LeetCode lose here — the technical bar is high but achievable; the LP bar is the actual filter.

The Bar Raiser is the structural innovation: one interviewer in your loop is a trained Bar Raiser from a different team whose explicit job is to veto offers that are technically OK but culturally questionable. The Bar Raiser leads the debrief and has effective veto power. You are not told who they are during the loop. The Bar Raiser is why "fine" candidates often get rejected — they didn't lower the bar, but they didn't raise it either.

STAR-method answers are non-negotiable, with strict expectations: explicit Situation, Task, YOUR-not-our Action, and quantified Result. Amazon dives deep on numbers — if your story has no concrete metric impact, the interviewer will probe until you produce one. For senior PM and PMT roles, expect a 6-page PR/FAQ writing assessment. Process timeline is typically 4-6 weeks.

"Hire" at Amazon = passes Bar Raiser veto, demonstrates concrete LP signal across at least 8-10 of the 16 Leadership Principles, and meets technical bar for the level. Amazon's explicit standard: every hire should raise the bar of the team they join.

Cultural pillars

What they're measuring you on, beyond the right answer

The values interviewers probe for. Each pillar is what they ask about, plus how they ask it.

Customer Obsession

Leaders start with the customer and work backwards. Every role at Amazon, every decision, traces back to customer outcome. The MOST probed Leadership Principle in interviews.

How they probe · At least one behavioral question per onsite round directly probes customer obsession. Looks for a story where you went above-and-beyond for a customer with concrete metric impact.

Ownership

Leaders act on behalf of the entire company, not just their team. They never say 'that's not my job.' They think long term and don't sacrifice long-term value for short-term results.

How they probe · Probes time you fixed something outside your scope, took responsibility for a team failure, or made a long-term call that hurt short-term metrics.

Bias for Action

Speed matters. Many decisions are reversible (two-way doors); calculated risk-taking is valued. Amazon's bias is against inaction. Looks for candidates who move fast without explicit hints.

How they probe · Asks about a calculated risk where speed was critical, or a time you were the first to take action when others waited.

Dive Deep

Leaders operate at all levels, stay connected to details, and audit frequently. They are skeptical when metrics and anecdote disagree. No task is beneath them.

How they probe · Drills into specific numbers in your STAR story — 'what was the latency before vs after?' If you can't produce concrete metrics, signal drops.

Deliver Results

Leaders focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, they rise to the occasion and never settle.

How they probe · Probes a time you missed a deadline (and what you did), or hit one despite obstacles. Concrete impact metric required.

Hire and Develop the Best (for senior+) / Earn Trust (for all levels)

At SDE3+ and PM senior+, Amazon probes how you've raised the bar through hiring and mentored others. Earn Trust shows up across all levels — give honest credit, listen attentively.

How they probe · Senior loops include explicit hiring/mentoring questions. Earn Trust probed via stories of building credibility across teams.

The full loop

Round-by-round, in the order they actually run

Reported pattern from candidate write-ups. Eliminating rounds are the ones where a single bad signal ends the loop.

01
Recruiter screen30 minNon-eliminating
career story, level expectation, LP intro
02
Online assessment90 minEliminating
2 coding problems + work simulation + LP work-style assessment
03
Technical Phone Screen60 minEliminating
1 coding problem + 1-2 LP questions
04
Onsite Coding 155 minEliminating
DSA problem + 2-3 LP questions
05
Onsite Coding Or Lld55 minEliminating
low-level design / OOP problem + LP questions
06
Onsite System Design55 minEliminating
distributed system design + LP questions
07
Onsite Hiring Manager55 minEliminating
deep behavioral, team fit, LP questions
08
Onsite Bar Raiser55 minEliminating
behavioral + 1 technical, Bar Raiser has veto power

Real questions, by round type

What candidates were actually asked

Curated from interview reports and company write-ups. Practise against any of these in a live mock.

SDE · Senior

Coding

Find the kth largest element in a stream of integers; multi-source variant
Implement a thread-safe in-memory key-value store with TTL eviction
Given a list of intervals, merge and find max overlapping count at any point
Word break II — return all valid sentences
Design and implement a snapshot-able set with O(1) snapshot
Given a 2D grid of warehouse cells, find shortest path for a robot with battery limit
LRU cache with concurrent reads and writes

System design

Design Amazon Prime Video — focus on encoding pipeline, CDN, recommendations
Design the Amazon order placement flow at peak Prime Day load
Design Alexa's wake-word detection + intent routing system
Design Amazon's product search ranking with personalization
Design a distributed rate limiter for AWS API Gateway

Behavioral

Tell me about a time you went above and beyond for a customer
Describe a calculated risk you took when speed was critical
Tell me about a time you missed a deadline. What did you do?
Describe a time you disagreed with your manager and how you resolved it
Tell me about the most innovative thing you've built — why was it innovative?
Describe a time you had to dive deep into data to find a root cause
Tell me about a time you took on something outside your scope

Product · Senior

product_strategy

Tell me about a customer feedback you followed through on
Tell me about a time you declined a customer request. Why?
Walk me through the most successful product you launched and the metric impact

analytical

Conversion on a checkout flow dropped 5% overnight. Walk me through diagnosis.
Define metrics for a new B2B feature in Amazon Business

stakeholder

Tell me about a stakeholder who refused to align. How did you build trust?
Describe defending a difficult decision against senior leadership

writing

PR/FAQ assignment: pitch a new feature for Amazon Fresh that increases SKU coverage by 30%

Data Science · Senior

sql_coding

Write SQL to compute weekly retention curves with cohort segmentation
Find products with anomalous return rates (>2 SD from category mean)

modeling

Design a forecasting system for warehouse demand with 7-day lookahead
Build an evaluation framework for a recommendation A/B test with novelty bias

Product sense

How would you measure success of a new Subscribe-and-Save feature?

Behavioral

Tell me about a model you shipped that failed in production. What did you do?

What rejects you · what advances you

The two patterns that decide every loop

Red flags

Vague behavioral answers with no concrete metrics ('it improved a lot')
'We' language throughout STAR — no clear individual action
Inability to recall numbers from a story you brought up
Repeating the same story across multiple LPs
Dismissing or arguing with the LP framework as 'corporate fluff'
No customer language in product/strategy answers — only metrics, no user empathy
Slow to act in problem-solving — 'I'd want to gather more data first' for everything
PR/FAQ document with no clear customer pain or measurable outcome

Advance signals

STAR answers with explicit Situation/Task/Action/Result and a hard number
Distinct stories per LP — at least 6-8 prepared for senior loops
Mentions long-term tradeoffs in 'deliver results' answers
Quantifies customer impact ('X latency drop saved Y conversions')
Articulates two-way-door vs one-way-door framing on risky decisions
Demonstrates skepticism with data — 'the metric showed X but I went into the warehouse and saw Y'
Shows hiring/mentoring impact at senior level (developed N people, raised bar)

Don't do

Reuse the same STAR story across multiple LP probes
Use 'we' without specifying your individual contribution
Show up without 8-10 distinct LP-aligned stories prepared
Submit a PR/FAQ that reads like a feature spec instead of starting with customer pain
Argue with the LP framework or roll your eyes at customer-obsession questions
Skip the Bar Raiser round in your prep — they have veto power and probe deepest
Forget to quantify — 'a lot' / 'significantly' lose signal

Compensation

Base salary bands by level

Junior

₹18–30L

Annual base

Mid

₹35–55L

Annual base

Senior

₹70–110L

Annual base

Staff+

₹110–180L

Annual base

Amazon India per Levels.fyi: SDE-2 (L5) median total ₹61L, SDE-3 (L6) median total ₹123L, range up to ₹213L for L7. RSUs are back-loaded (5-15-40-40 over 4 years), which is unique to Amazon and a frequent negotiation pain point. Sign-on bonus typically covers Y1 and partial Y2 to offset back-loaded vest. India offices: Bangalore (largest), Hyderabad, Chennai, Pune, Delhi/NCR. Amazon TC is generally below Google/Meta at equivalent level but team scope and Indian-market relevance are often larger.

Process

What to expect after each round

Typical timeline

~5 weeks

Recruiter-screen → offer

Reapply window

6 months

After a final-round rejection

Feedback practice

Generic outcome only. Recruiters may share which LPs were a stretch but not full feedback.

“Thanks for your time. Your recruiter will follow up with next steps after the debrief, typically within 5-7 business days. The debrief is led by the Bar Raiser.”

Verified profile

Last verified Mon Apr 27 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · 6 sources

View sources