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Amazon·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026

Summary

Amazon SWE interview with an OOD question about playlists and guides. Pretty focused session, one meaty design problem with a follow-up I didn't fully nail.

Questions Asked (2)

Q1

Design a playlist system where each playlist contains multiple guides. Implement addGuide (takes a guide ID, user ID, and playlist ID), vote (takes guide ID, user ID, playlist ID, and an upvote/downvote value, both returning void), and getPlaylist (returns all guides in a given playlist sorted by votes descending, with timestamp as a tiebreaker).

System DesignData ModelingAlgorithms & Data Structures
Author's notes

The core functions weren't too bad to sketch out.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design the data model and API contracts. Discuss how to efficiently handle votes and sorting, considering data structures and storage options. Finally, address scalability, consistency, and potential optimizations.

Pro tip: Demonstrate awareness of Amazon's leadership principles by emphasizing customer obsession (e.g., low-latency playlist retrieval) and ownership (e.g., handling edge cases like duplicate votes).

1. Clarify Requirements

Ask about scale (number of playlists, guides, votes), read/write ratio, consistency needs, and whether votes can be changed or retracted.

2. Design Data Model

Define entities: Playlist, Guide, User, and Vote. Decide on storage (e.g., relational vs. NoSQL) and how to represent relationships and vote counts.

3. Define API and Core Logic

Specify addGuide, vote, and getPlaylist signatures. For vote, consider idempotency and updating aggregate counts. For getPlaylist, outline sorting by votes desc and timestamp asc.

4. Address Scalability and Performance

Discuss indexing, caching, sharding, and asynchronous processing. Consider how to handle hot playlists and high write throughput.

5. Handle Edge Cases and Trade-offs

Cover duplicate votes, vote changes, tie-breaking, and consistency vs. availability. Mention monitoring and failure recovery.

Key Points to Mention

  • Choice of data store (SQL vs NoSQL) and schema design for efficient queries
  • Indexing strategy for fast retrieval of guides sorted by votes and timestamp
  • Caching frequently accessed playlists to reduce latency
  • Idempotent vote handling and preventing duplicate votes per user per guide
  • Scalability considerations: sharding by playlist ID, read replicas, and eventual consistency
  • Trade-offs between strong and eventual consistency for vote counts

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

How would you extend the system to support different sorting strategies for getPlaylist in the future?

System DesignTechnical Trade-offs
Author's notes

I said something about pulling the sorting logic out and using method overrides, which felt right directionally but vague.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the current implementation and requirements, then propose a design that decouples sorting from the core playlist retrieval logic. Discuss trade-offs between different approaches (e.g., strategy pattern vs. comparator injection) and emphasize extensibility, maintainability, and performance.

Pro tip: Mention Amazon's leadership principles like 'Customer Obsession' and 'Invent and Simplify' by tying sorting strategies to customer needs and avoiding over-engineering. Also, highlight the importance of backward compatibility and incremental rollout.

1. Clarify Requirements and Current State

Ask questions to understand the existing getPlaylist implementation, expected sorting criteria, and non-functional requirements like performance and scalability. Confirm whether sorting should be client-driven or server-driven.

2. Identify Extension Points

Determine where sorting logic can be abstracted, such as introducing a SortStrategy interface or using a Comparator. Ensure the core playlist retrieval remains unchanged.

3. Propose Design Options

Present multiple approaches (e.g., Strategy pattern, Factory, or configuration-driven) and compare them in terms of flexibility, complexity, and performance. Recommend one based on trade-offs.

4. Address Implementation Details

Discuss how to integrate the chosen design: dependency injection, configuration management, and API changes (e.g., adding a sort parameter). Consider caching and pagination implications.

5. Plan for Testing and Rollout

Outline unit and integration tests for each strategy, and propose a phased rollout with feature flags to mitigate risks. Mention monitoring and metrics to track usage and performance.

Key Points to Mention

  • Strategy pattern or Comparator injection to encapsulate sorting algorithms
  • Open/Closed Principle: open for extension, closed for modification
  • Trade-offs: flexibility vs. complexity, performance overhead of dynamic sorting
  • API design: adding optional sort parameters with sensible defaults
  • Backward compatibility and versioning to avoid breaking existing clients
  • Testing strategies: unit tests for each sort, integration tests for end-to-end
  • Amazon Leadership Principles: Customer Obsession, Invent and Simplify, Bias for Action

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.