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Amplitude·Software Engineer·Onsite - System Design / Architecture·Intermediate

IntermediatePrefer not to say
May 2026

Summary

System design round at Amplitude for a software engineer role. The prompt was building a collaborative todo list app, which sounds simple but they pushed into real-time sync territory pretty fast and that's where things got interesting.

Questions Asked (4)

Q1

What are the core product requirements and user flows for a collaborative todo list sharing application?

Product Sense & IdeationSystem Design
Author's notes

Started here and it felt like a warmup but I almost rushed through it.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the product vision and target users, then break down core requirements into functional and non-functional categories, and finally map out the primary user flows. Emphasize how the design supports collaboration, real-time updates, and scalability, aligning with Amplitude's data-driven product culture.

Pro tip: Tie your answer to Amplitude's focus on product analytics by suggesting instrumentation of key user actions (e.g., task creation, sharing, completion) to measure engagement and drive iterative improvements. This shows you think beyond features to how the product succeeds.

1. Clarify Scope and Users

Ask clarifying questions to define the target users (e.g., teams, families) and the core value proposition (e.g., simple sharing vs. advanced project management). This ensures your answer is focused and relevant.

2. Define Core Product Requirements

List functional requirements (e.g., create/edit/delete tasks, assign users, due dates, real-time sync, notifications) and non-functional requirements (e.g., scalability, latency, offline support, security).

3. Map Primary User Flows

Outline the main user journeys: onboarding and list creation, inviting collaborators, adding/editing tasks, completing tasks, and viewing activity history. Highlight how collaboration is enabled at each step.

4. Address Collaboration and Real-Time Aspects

Explain how multiple users interact concurrently (e.g., conflict resolution, presence indicators, live updates) and the underlying system design considerations (e.g., WebSockets, CRDTs, event sourcing).

5. Prioritize and Iterate

Suggest an MVP scope and future enhancements, and mention how you would measure success using analytics (e.g., DAU, task completion rate) to guide iterations.

Key Points to Mention

  • Real-time synchronization and conflict resolution strategies (e.g., operational transforms, CRDTs)
  • User authentication and permission models (e.g., owner, editor, viewer roles)
  • Notification system for task assignments, due dates, and mentions
  • Offline support and data consistency when connectivity is restored
  • Scalability considerations for handling many concurrent users and lists
  • Analytics instrumentation to track user engagement and feature adoption

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

Q2

Design the backend APIs for creating todo lists, sharing them with other users, and managing individual todo items.

API & IntegrationsSystem DesignTechnical Trade-offs
Author's notes

This is where I felt most comfortable.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints (e.g., scale, sharing permissions, real-time needs). Then design a RESTful API with clear resource modeling, covering authentication, authorization, and data consistency. Finally, discuss trade-offs and potential extensions like pagination, versioning, and rate limiting.

Pro tip: Demonstrate awareness of Amplitude's product context by emphasizing data integrity and access control, and mention how you'd instrument the API for analytics (e.g., tracking usage events) to align with the company's data-driven culture.

1. Clarify Requirements

Ask questions to understand scale, sharing semantics (read-only vs. collaborative), and non-functional requirements like latency and consistency.

2. Model Resources and Endpoints

Define core resources (users, todo lists, items, shares) and design RESTful endpoints with appropriate HTTP methods and status codes.

3. Address Security and Permissions

Outline authentication (e.g., OAuth2) and authorization (e.g., role-based access control) for sharing and item management.

4. Discuss Data Consistency and Scalability

Explain how to handle concurrent updates, pagination, and potential caching or sharding strategies.

5. Evaluate Trade-offs and Extensions

Compare design choices (e.g., REST vs. GraphQL, sync vs. async sharing) and suggest future improvements like webhooks or audit logs.

Key Points to Mention

  • Resource modeling: users, todo lists, items, and shares as separate entities with clear relationships.
  • RESTful endpoint design: use nouns for resources, proper HTTP verbs, and status codes (e.g., POST /lists, GET /lists/{id}, PUT /lists/{id}/items/{itemId}).
  • Authentication and authorization: OAuth2 for auth, and permission checks for sharing (e.g., owner, editor, viewer roles).
  • Data consistency: use optimistic locking or versioning to handle concurrent edits, and transactions for atomic operations.
  • Pagination and filtering: implement limit/offset or cursor-based pagination for listing items, and query parameters for filtering.
  • Trade-offs: discuss REST vs. GraphQL, synchronous vs. asynchronous sharing notifications, and idempotency for safe retries.

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

Q3

Design a database schema to store users, todo lists, permissions, and individual items.

Data ModelingSystem Design
Author's notes

Pretty standard relational schema.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and access patterns, then design normalized tables for users, lists, items, and permissions with appropriate relationships and indexes. Discuss trade-offs between normalization and denormalization, and how the schema supports common queries like fetching a user's lists or checking permissions.

Pro tip: Mention that permissions can be modeled as a separate table with a role-based or resource-based approach, and consider using an enum for permission types to keep it flexible. Also, highlight the importance of indexing foreign keys and frequently queried columns for performance.

1. Clarify Requirements

Ask about expected scale, read/write patterns, and whether permissions are role-based or per-resource. Confirm if lists can be shared and if items can have sub-items.

2. Identify Core Entities

Define the main tables: Users, Lists, Items, and Permissions. Determine primary keys and essential attributes for each.

3. Define Relationships

Establish foreign keys: Lists belong to Users (owner), Items belong to Lists, and Permissions link Users to Lists with a permission level. Consider many-to-many for shared lists.

4. Design Permissions Model

Decide between role-based (e.g., owner, editor, viewer) or granular permissions. Create a Permissions table with user_id, list_id, and permission_type, and discuss inheritance or cascading.

5. Optimize and Discuss Trade-offs

Add indexes on foreign keys and frequently filtered columns. Discuss normalization vs. denormalization for performance, and how to handle soft deletes or audit trails.

Key Points to Mention

  • Normalization to reduce redundancy, with foreign keys enforcing referential integrity.
  • Indexing strategy: indexes on foreign keys (e.g., list_id in items) and composite indexes for common queries.
  • Permission model: separate table with user_id, list_id, and role/permission enum; consider role-based access control (RBAC).
  • Scalability considerations: sharding by user_id or list_id, and using UUIDs vs. auto-increment IDs.
  • Data integrity: cascading deletes or soft deletes to handle list/item removal.
  • Query patterns: efficient retrieval of a user's lists, items in a list, and permission checks.

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

Q4

How would you support real-time updates so all collaborators see changes to a shared list immediately?

System DesignTechnical Trade-offs
Author's notes

This is the one I should've prepared more for.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements such as scale, latency, and consistency needs, then propose a real-time communication mechanism like WebSockets or Server-Sent Events, and discuss how to handle state synchronization, conflict resolution, and scalability. Conclude by weighing trade-offs between different approaches and explaining how you would ensure reliability and performance.

Pro tip: Demonstrate awareness of operational concerns by mentioning how you would monitor connection health, handle reconnections, and degrade gracefully under load—this shows you think beyond the happy path.

1. Clarify Requirements

Ask about expected number of collaborators, update frequency, latency tolerance, and consistency requirements to scope the solution appropriately.

2. Choose Real-Time Transport

Select a transport like WebSockets (bidirectional) or Server-Sent Events (unidirectional) based on whether clients need to send updates or just receive them.

3. Design State Synchronization

Decide how to propagate changes: use operational transforms (OT) or conflict-free replicated data types (CRDTs) to handle concurrent edits and ensure eventual consistency.

4. Address Scalability and Reliability

Plan for horizontal scaling with a pub/sub system (e.g., Redis, Kafka), handle reconnections with exponential backoff, and ensure message ordering and delivery guarantees.

5. Discuss Trade-offs

Compare approaches (e.g., WebSockets vs. polling, OT vs. CRDT) in terms of complexity, latency, consistency, and cost, and justify your choices.

Key Points to Mention

  • WebSockets vs. Server-Sent Events vs. long polling: trade-offs in latency, overhead, and browser support
  • Conflict resolution strategies: operational transforms (OT) vs. conflict-free replicated data types (CRDTs)
  • Scalability: using a pub/sub layer (e.g., Redis Pub/Sub, Kafka) to fan out updates across multiple server instances
  • Reliability: handling disconnections, reconnections with exponential backoff, and message acknowledgment/retry
  • Consistency models: eventual consistency vs. strong consistency and their impact on user experience
  • Performance optimizations: batching updates, delta compression, and throttling to reduce network load

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