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Citadel·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Citadel software engineer interview with a coding question around stateful counters. Pretty focused, not much fluff.

Questions Asked (1)

Q1

Implement a counter function that tracks how many times each key has been invoked and returns the current count for that key.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

Seemed straightforward at first and I almost over-engineered it with a class.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements: is this a simple in-memory counter or does it need to be thread-safe, persistent, or distributed? Then present a clean implementation using a hash map, and discuss trade-offs like concurrency, memory, and API design. Finally, mention potential extensions like TTL or sharding for scale.

Pro tip: Demonstrate awareness of concurrency by noting that a plain hash map is not thread-safe and proposing alternatives like ConcurrentHashMap or atomic operations, which is crucial for high-frequency trading systems at Citadel.

1. Clarify Requirements

Ask about expected scale, concurrency needs, persistence, and whether keys are strings or other types. This shows you think before coding.

2. Design the Data Structure

Choose a hash map for O(1) average time complexity. Discuss potential collisions and resizing.

3. Implement the Counter

Write a function that increments the count for a given key and returns the new count. Handle missing keys by initializing to 0.

4. Address Concurrency

If needed, make it thread-safe using locks, ConcurrentHashMap, or atomic operations. Discuss performance implications.

5. Discuss Trade-offs and Extensions

Talk about memory usage, eviction policies, distributed counters, and API design (e.g., separate increment and get methods).

Key Points to Mention

  • Time and space complexity: O(1) average for increment and get, O(n) space for n unique keys.
  • Thread safety: use ConcurrentHashMap or synchronized blocks; avoid race conditions.
  • Memory management: consider eviction policies like LRU for unbounded keys.
  • Distributed scenarios: sharding, consistent hashing, or using Redis for shared counters.
  • API design: whether to combine increment and get or separate them for flexibility.
  • Error handling: what if key is null? Should it throw or handle gracefully?

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