Amazon SDE-2
Summary
I interviewed for an SDE-2 role at Amazon and was successfully selected. The interview process consisted of multiple rounds covering Data Structures & Algorithms, Low-Level Design, High-Level Design, and Amazon's leadership principles.
Full Experience
All rounds had 2-3 questions based on Amazon leadership principles.
Round 1 - 2 DSA questions:
1 -> Search in rotated sorted array
2 -> Variation of next greater element
Round 2 - LLD: Design an order processing engine to handle multiple orders where one order can come multiple times due to network issues and retries.
Round 3 - HLD + Resume: Brief discussion on resume and HLD on designing an AI-based summarization solution for contact center at Amazon.
Round 4 - HLD:
Q: "Design a simplified version of Twitter with three core features:
1: Tweet creation – Store user-generated posts.
2: Feed aggregation – Retrieve and display tweets from followed accounts in an efficient manner with sub-second latency.
3: Popular Tweets in Feed – Surface high-engagement tweets based on popularity ranking within the user's network.
System components needed: Ingestion, Tweet Service, Feed Service, Data Persistence, Popularity Ranker, and API layer.
Verdict: Selected
Compensation: https://leetcode.com/discuss/post/7622800/amazon-sde-2-offer-by-anonymous_user-hxtk/
Interview Questions (4)
Search in Rotated Sorted Array
I was asked a DSA question related to searching for an element in a rotated sorted array.
Design an Order Processing Engine
I had an LLD round focused on designing an order processing engine. The engine needed to handle multiple orders, specifically addressing scenarios where a single order might arrive multiple times due to network issues and retries.
Design an AI-based Summarization Solution for Contact Center
During an HLD round, I discussed my resume and then proceeded to design an AI-based summarization solution for a contact center at Amazon.
Design a Simplified Twitter
I was asked to design a simplified version of Twitter with the following three core features:
1: Tweet creation – Storing user-generated posts.
2: Feed aggregation – Efficiently retrieving and displaying tweets from followed accounts with sub-second latency.
3: Popular Tweets in Feed – Surfacing high-engagement tweets based on popularity ranking within the user's network.
Key system components to consider included Ingestion, Tweet Service, Feed Service, Data Persistence, Popularity Ranker, and an API layer.