Rounds 1–2 are fully visible · Round 3+ unlocked with a free account
Advanced Data StructuresCache DesignLP: Dive Deep
Hard coding problem with LP integration. At L6, Amazon expects production-quality code: correct edge cases, explicit complexity analysis, and self-introduced test cases — none of these are prompted. You're also expected to identify when a simpler solution exists before optimizing, since Insist on the Highest Standards cuts both ways: gold-plating a simple problem is also a signal.
What to expect
- ›LP: 'Describe the most complex distributed debugging problem you've worked through (Dive Deep)' — they want tool names, the hypothesis chain, and what the root cause turned out to be
- ›Coding: e.g., 'LFU Cache — O(1) get, put, and eviction' using two HashMaps keyed by value and frequency, plus a doubly-linked list per frequency bucket
- ›Self-introduce test cases before being asked: null input, single element, all keys at the same frequency, capacity-1 cache — this signals production thinking
- ›Trap: solving the problem correctly but failing to discuss when LFU is worse than LRU (bursty access patterns) — L6 answers show awareness of where your solution breaks
Practice on KnowEase.AI
Distributed LockingCAP TheoremScalabilityCost OptimizationA/B Testing
Large-scale HLD with deep follow-up on every component. At L6, you drive the conversation — the interviewer's job is to follow your lead and probe for gaps, not to hand you a structure. Capacity planning, failure modes, and cost optimization should surface unprompted in the first 20 minutes. Amazon-specific system design prompts reported in 2024–2025 include inventory reservation under flash-sale load and A/B experimentation platforms with traffic splitting and metrics pipelines.
What to expect
- ›e.g., 'Design Amazon's inventory reservation system for Prime Day flash sales' — distributed locking (Redis SETNX or DynamoDB conditional writes), optimistic concurrency for catalog reads, rollback on payment failure, thundering-herd prevention via queue-based checkout
- ›e.g., 'Design an A/B experimentation platform for Amazon' — assignment service that splits traffic deterministically by user_id, streaming pipeline collecting experiment metrics, manual override so QA can force users into a specific variant, mutual exclusivity layer so a user doesn't land in contradictory experiments simultaneously
- ›CAP theorem applied: 'Strong consistency for reservation state, eventual consistency for product catalog — here's why they differ and what failure scenario each choice accepts'
- ›Trap: designing the happy path and waiting for the interviewer to ask about failure — at L6 they expect you to enumerate your system's failure modes before they ask; if they have to prompt you, it's a yellow flag
Practice on KnowEase.AI
API DesignStrategy PatternVersioningError ContractsIdempotency
Object-oriented design or API design for an internal Amazon service. The emphasis is on interfaces other teams can consume safely — idempotency, versioning contracts, and explicit error models matter more than internal implementation elegance. Amazon's fulfillment and logistics domain appears frequently: routing services, order lifecycle APIs, and warehouse management system interfaces.
What to expect
- ›e.g., 'Design the API for Amazon's fulfillment routing service' — idempotent routing requests (so retries don't double-ship), explicit v1/v2 versioning with backward-compatibility guarantees, error contracts that distinguish transient failures from permanent rejections
- ›Class hierarchy: Strategy pattern for routing algorithms (FBA, Fulfilled by Seller, Fresh, Amazon Logistics) so new fulfillment types extend without modifying the router core
- ›API versioning: how do you deprecate v1 without breaking the 40 internal teams that integrated against it?
- ›Trap: designing an API that works for the happy path but has no defined behavior when a fulfillment center goes offline mid-order — the interviewer will ask, and 'handle it in the client' is not an answer
LP: Disagree and CommitLP: Highest StandardsLP: Hire and DevelopTechnical Leadership
Intensive behavioral round — 3–4 LP stories in 60 minutes. At L6, the scope of every story must be cross-team or org-wide. Interviewers probe for leadership impact, not individual contribution. This is also where the Disagree and Commit LP gets tested in full: Amazon wants engineers who push back with data, lose the argument, and still execute with full commitment — and can tell that story cleanly.
What to expect
- ›LP: 'Tell me about a time you disagreed with a VP or Director on a technical direction — what data did you bring, how did the conversation go, and what did you do after the decision went against you? (Disagree and Commit)' — candidates who can't name a real disagreement or who glossed over the 'commit' part both fail this
- ›LP: 'Describe a time you set a new engineering standard that your entire organization adopted (Insist on the Highest Standards)' — team-level standards are SDE-2 answers; L6 scope means org-wide
- ›LP: 'How have you actively grown the next generation of senior engineers — not just mentored them, but changed the trajectory of their careers? (Hire and Develop the Best)'
- ›Expect 5-why follow-ups on every story — 'Why did you pick that metric?', 'What would have happened if you hadn't acted?', 'What did the person whose idea got rejected do next?'
LP: Full SpectrumSystem Design Under PressureJudgmentTechnical Breadth
At L6, the Bar Raiser is mandatory and qualitatively different from lower levels. They are validating that you are in the top quartile of L6 SDEs globally — not just competent. They will deliberately find the edges of your knowledge: areas where your mental model breaks down, LP stories that don't hold up under follow-up, system designs you haven't thought through. Novel design problems are common in this slot — they want to see how you think when you can't fall back on a prepared answer.
What to expect
- ›Technical breadth check: 'Walk me through a recent paper or system architecture you studied outside of work — what was the key insight and how would you apply it at Amazon scale?'
- ›LP stress test: 'You gave a strong answer on Ownership — now tell me about a time taking ownership backfired and what you'd do differently'
- ›Novel design prompt: e.g., 'Design a DropBox-like file sync service for Amazon's internal document management' — evaluating structured problem decomposition, not memorized answers
- ›Trap: treating the Bar Raiser like a standard coding or design round — they are explicitly looking for how you think when pushed into unfamiliar territory; clean but shallow answers lose to messy but genuine ones
Technical VisionRoadmapStrategic ThinkingLP: Ownership
Strategic alignment with the hiring manager — often a Principal or Sr. Principal Engineer or a Director. At L6, this round probes whether you can own a technology pillar independently: setting multi-year direction, managing technical debt at scale, and aligning stakeholders across orgs. The HM is also evaluating whether you'll raise their team's bar, not just fill a headcount.
What to expect
- ›How do you approach setting 3-year technical direction for a domain area when business priorities shift every quarter?
- ›Walk me through a time you retired a major system — how did you sequence the migration, handle backward compatibility, and get 15 teams to cut over without a coordinated shutdown
- ›What's a technology bet you'd make for Amazon's core business in the next 5 years and what's the counterfactual risk if you're wrong?
- ›Trap: framing your answers around individual delivery ('I built X') rather than organizational enablement ('I changed how the org builds X') — at L6, the HM is hiring someone to multiply the team's output, not add to it
