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

Senior
Jun 2026

Summary

System design round at Anthropic for a software engineering role. The whole thing was one meaty problem about building a multithreaded web crawler, and it went deeper than I expected into concurrency and shutdown behavior.

Questions Asked (1)

Q1

Design and implement a multithreaded web crawler. Given a starting URL and an interface that returns all URLs on a page, crawl everything under the same hostname in parallel without revisiting any URL. Walk through your synchronization strategy and how you'd shut the system down cleanly.

System DesignTechnical Trade-offsAlgorithms & Data Structures
Author's notes

I started with the obvious stuff, thread pool, a shared visited set, a work queue.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a design using a thread-safe queue and a concurrent set for visited URLs. Explain the synchronization strategy (e.g., locks, atomics) and how to detect completion and shut down cleanly. Finally, discuss trade-offs and potential improvements.

Pro tip: Demonstrate awareness of backpressure and politeness policies (e.g., rate limiting per host) to show you consider real-world crawling constraints beyond just parallelism.

1. Clarify Requirements and Constraints

Ask about scale, expected page count, depth limits, politeness (robots.txt, rate limiting), and whether the interface is thread-safe. Confirm that only same-host URLs should be crawled.

2. Design Core Data Structures

Use a thread-safe queue (e.g., LinkedBlockingQueue) for URLs to crawl and a concurrent set (e.g., ConcurrentHashMap.newKeySet()) for visited URLs. Ensure atomic check-and-add to avoid duplicates.

3. Implement Worker Threads and Synchronization

Create a fixed thread pool. Each worker loops: take URL from queue, fetch page, extract URLs, filter same-host, and for each new URL atomically add to visited and enqueue. Use a counter or active task count to track pending work.

4. Handle Shutdown and Completion Detection

Use a poison pill or a completion flag when the queue is empty and no active tasks. Ensure all threads terminate gracefully, possibly with a timeout. Discuss clean shutdown on error or interruption.

5. Discuss Trade-offs and Optimizations

Mention trade-offs: thread pool size vs. context switching, lock contention, memory usage of visited set, and potential for distributed crawling. Suggest improvements like async I/O or partitioning by host.

Key Points to Mention

  • Thread-safe data structures: concurrent queue and set with atomic operations.
  • Synchronization primitives: locks, atomics, or concurrent collections to avoid race conditions.
  • Completion detection: tracking active tasks or using a poison pill to signal termination.
  • Politeness and rate limiting: respecting robots.txt and avoiding overwhelming the host.
  • Error handling: dealing with network failures, timeouts, and retries without deadlock.
  • Scalability considerations: thread pool sizing, backpressure, and potential distributed design.

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