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

IntermediatePrefer not to say
Jul 2026

Summary

One system design question for a software engineer role at Whatnot. Short and to the point, nothing else to report.

Questions Asked (1)

Q1

Design a platform like LeetCode from scratch.

System DesignTechnical Trade-offsAPI & Integrations
Author's notes

Classic system design prompt but there's actually a lot hiding under the surface.

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AI HintsAI Generated

Suggested Approach

Start by clarifying functional and non-functional requirements, then design the high-level architecture covering core components like problem repository, code execution, and submission handling. Dive into critical components such as the code execution engine, emphasizing scalability, security, and trade-offs.

Pro tip: Emphasize the importance of isolating code execution using containers or microVMs to prevent security breaches, and discuss how to handle resource constraints and scaling for concurrent submissions.

1. Clarify Requirements

Ask questions to understand the scope: user roles (admin, user), features (problem browsing, code editing, submission, judging), scale (number of users, submissions per day), and constraints (latency, security).

2. High-Level Design

Outline the main components: web servers, database, code execution service, message queue, and caching. Sketch a simple architecture diagram and explain data flow.

3. Deep Dive into Key Components

Focus on the code execution engine: how to run untrusted code securely (sandboxing), manage resources (CPU, memory), and scale horizontally. Discuss database schema for problems and submissions.

4. Address Trade-offs and Scalability

Discuss trade-offs like synchronous vs asynchronous judging, SQL vs NoSQL for different data, and strategies for scaling (caching, sharding, load balancing).

5. Summarize and Identify Bottlenecks

Recap the design, highlight potential bottlenecks (e.g., code execution service), and suggest monitoring and optimization approaches.

Key Points to Mention

  • Secure code execution using sandboxing (Docker, gVisor, Firecracker) with resource limits.
  • Asynchronous processing of submissions via message queues (e.g., RabbitMQ, Kafka) to handle spikes.
  • Database design: SQL for relational data (users, problems), NoSQL for submissions if high write throughput.
  • Caching strategies for problem statements and leaderboards (Redis, CDN).
  • API design for problem retrieval, submission, and status checking (RESTful or GraphQL).
  • Scalability considerations: horizontal scaling of execution workers, auto-scaling, and load balancing.

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