crusoe·Software Engineer·Onsite - System Design / Architecture·Senior

Senior

Jun 2026

Summary

System design round at Crusoe for a software engineering role. The whole thing was one big question about building a Slack-like messaging platform, which sounds manageable until you realize how many moving parts they actually want you to cover.

Questions Asked (1)

Design a team messaging system similar to Slack. Your design should cover workspaces, public and private channels, direct messages, threaded replies, presence and typing indicators, message persistence and search, push notifications, file attachments, and how you'd scale it to support many concurrent users with low-latency delivery.

System DesignTechnical Trade-offsData Modeling

Author's notes

This is basically a full system design gauntlet crammed into one question.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design the core data model and high-level architecture. Focus on the message delivery pipeline and storage strategy, and finally discuss scaling and trade-offs.

Pro tip: Emphasize the separation of concerns: use a pub/sub system for real-time delivery and a separate store optimized for search. This shows you understand how to decouple components for scalability and performance.

1. Clarify Requirements and Scale

Ask questions to understand expected user count, message volume, latency requirements, and key features. Define the scope and constraints.

2. High-Level Architecture

Sketch the main components: clients, API gateway, WebSocket servers, message service, presence service, notification service, and storage layers.

3. Data Model and Storage

Design schemas for workspaces, channels, messages, threads, and attachments. Choose appropriate databases (e.g., Cassandra for messages, Elasticsearch for search).

4. Real-Time Delivery and Presence

Explain how to use WebSockets and a pub/sub system (e.g., Redis, Kafka) for low-latency message delivery, typing indicators, and presence updates.

5. Scaling and Trade-offs

Discuss horizontal scaling, sharding, caching, and trade-offs between consistency and availability. Address bottlenecks and failure handling.

Key Points to Mention

Use WebSockets for persistent connections and real-time updates.
Employ a pub/sub system (e.g., Redis Pub/Sub, Kafka) for message fan-out.
Store messages in a distributed database like Cassandra for high write throughput.
Index messages in Elasticsearch for efficient search.
Handle presence and typing indicators with ephemeral storage (e.g., Redis).
Scale WebSocket servers horizontally with a load balancer and sticky sessions.

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