Amazon SDE2 Interview Experience February 2026 Offer Received

*

Status: SDE2 at Mid-sized Tech *

Experience: 4 Years *

Position: SDE2 (L5) at Amazon *

Date: February 2026 --- ### Online Assessment (OA) Two coding questions + Work Style Simulation

*

Status: SDE2 at Mid-sized Tech *

Experience: 4 Years *

Position: SDE2 (L5) at Amazon *

Date: February 2026 --- ### Online Assessment (OA) Two coding questions + Work Style Simulation. 1.

Question 1: Variation of

Merge Intervals. 2.

Question 2:

Graph/Dijkstra based. 3.

Simulation: Focus heavily on

Ownership and

Bias for Action. Don't just pick the "safe" answer; pick the one that delivers for the customer. --- ### Virtual Onsite (4 Rounds) ####

Round 1 Data Structures & Algorithms *

Leadership Principles (LP): Customer Obsession and Ownership. *

Technical:

LeetCode 1094 (Car Pooling) variant. *

Details: After solving with a TreeMap ($O(N \log N)$), the interviewer pushed for an $O(N)$

solution using a difference array. We then discussed how to scale this if the "trips" data was stored in a distributed DB. ####

Round 2 System Design (HLD) *

LP: Learn and Be Curious and Dive Deep. *

Technical:

Design a Real-Time Error Log Monitoring System. *

Details: *

Requirements: Handle 1M+ writes/sec, sub-second alerting. *

Architecture: Used Kafka for the ingestion layer, Flink for windowed aggregation, and Elasticsearch for querying. *

Deep Dive: We spent 15 minutes on backpressure—what happens when the consumer can't keep up with the log spikes? ####

Round 3 Object-Oriented Design (LLD) *

LP: Bias for Action and Disagree and Commit. *

Technical:

Design a Vending Machine Leasing System. *

Details: Focused on the relationship between VendingMachine, LeaseAgreement, and PaymentStrategy. *

Key: Used the

State Pattern to handle machine conditions (Idle, Out of Stock, Maintenance). The interviewer looked for clean interfaces and extensibility. ####

Round 4 The Bar Raiser *

LP: Insist on the Highest Standards and Deliver Results. *

Technical:

Distributed Rate Limiter. *

Details: * Started with the

Token Bucket algorithm logic. * Moved into the implementation: How to handle concurrency using

Redis Lua scripts to ensure atomicity. * The LP part was intense; they kept asking for specific data points and metrics for every "Result" I mentioned. ---

Result: Offer.