# High-Score (Bugfree) Amazon SDE-2 Interview Experience: In-Person Loop + Virtual Bar Raiser Amazon interview cover # High-Score (Bugfree) Amazon SDE-2 Interview Experience A concise write-up of my Amazon SDE-2 interview loop — applied via referral with ~2 years of fintech full-stack experience. The process included an online assessment, a pause by the recruiter due to location, reconnection for Hyderabad onsite scheduling, a 4-round in-person loop, and a virtual bar-raiser. Final status: selected. ## Quick timeline - Applied via referral (2 years fintech, full-stack) - Online assessment (OA): straightforward - Recruiter paused because of location, later reconnected for Hyderabad - In-person loop (3 rounds) + virtual bar-raiser (4th round) - Final: selected --- ## Interview breakdown (round-by-round) Round 1 — LP + Coding - Leadership Principles (LP) behavioral questions - Coding problems: "Max Points from Cards" and "Asteroid Collision" - Notes: Did a dry run on Asteroid Collision, caught a bug, fixed it during the interview — good debugging demonstration Round 2 — LP + Low-Level Design (LLD) - LP discussion - LLD: Tic-Tac-Toe - Covered required entities, class design, and class diagram - Implemented the game-over check method in C++ Round 3 — LP + High-Level Design (HLD) - LP behavioral questions - HLD: Event Booking System (architecture, components, scalability considerations) Round 4 (Bar Raiser — virtual) — LP + Coding - LP-focused behavioral assessment by the bar raiser - Coding problems: "House Robber II" and "Boats to Save People" - House Robber II: circular DP variant — deal with circular constraint by splitting into two linear runs - Boats to Save People: two-pointer greedy approach to pair lightest and heaviest --- ## What worked well - Clear LP stories: used STAR format (Situation, Task, Action, Result) and tied examples to Amazon's principles - Dry runs: doing a hand-simulation helped catch a bug live (shows attention to detail) - LLD/ HLD clarity: focusing on entities, APIs, data flow, fault tolerance, and scaling trade-offs - Language comfort: implemented C++ method when asked — be comfortable in at least one language ## Quick tips if you're preparing for a similar loop - Prepare 6–8 strong LP stories mapped to Amazon's Leadership Principles; rehearse concise STAR answers - Practice dry runs for coding problems — simulate inputs/outputs and edge cases on paper - For LLD: sketch entities, relationships, responsibilities, and one or two key methods - For HLD: discuss capacity, data partitioning, caching, consistency, and failure scenarios - Know common patterns: two-pointers, stacks, DP (including circular DP), and greedy strategies --- ## Final notes Recruiter logistics questions (compensation, notice period, location) were asked toward the end and I accepted the offer. The combination of strong LP storytelling, careful dry runs during coding, and clear design explanations helped secure the role. Good luck — and debug your dry run! #AmazonInterview #SystemDesign #SoftwareEngineering