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Xai·Software Engineer·Onsite - Coding / Algorithms·Senior

SeniorPrefer not to say
Jun 2026

Summary

xAI SWE onsite had a classic multi-level key-value store problem that kept escalating. each level added a new constraint and by the end i was basically building a mini database from scratch.

Questions Asked (1)

Q1

Design and implement an in-memory key-value store with set, get, and delete operations. Then extend it progressively: add TTL support, then transactional semantics with begin/commit/rollback, then snapshot and restore. For each level, explain your data structure choices, operation time complexity, and how you reused code from previous levels.

System DesignAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

The first level felt almost too easy and i said so out loud which in retrospect was dumb.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and assumptions, then walk through each level incrementally, explaining data structure choices, time complexity, and code reuse. Emphasize how each extension builds on the previous one without major refactoring, and discuss trade-offs.

Pro tip: Mention that TTL can be implemented lazily with periodic cleanup, and that transactions can use a command log or copy-on-write for rollback. Also, highlight that snapshots can be done via serialization or persistent data structures to avoid deep copies.

1. Clarify requirements and assumptions

Ask about expected scale, concurrency, persistence, and whether operations need to be thread-safe. Define the API and error handling.

2. Design basic key-value store

Choose a hash map for O(1) average set/get/delete. Discuss collision handling and resizing. Mention alternative structures like balanced trees for ordered operations.

3. Add TTL support

Store expiration timestamps alongside values. Use lazy deletion on access and/or a background thread for periodic cleanup. Discuss time complexity and memory overhead.

4. Implement transactions

Use a transaction log or copy-on-write to track changes. On commit, apply changes atomically; on rollback, discard. Discuss isolation levels and concurrency control.

5. Add snapshot and restore

Serialize the store to a durable format or use persistent data structures for efficient snapshots. Discuss trade-offs between full copy and incremental snapshots.

Key Points to Mention

  • Hash map for O(1) average operations, with discussion of worst-case O(n) and alternatives.
  • TTL implementation: lazy expiration vs. active expiration, and impact on memory and latency.
  • Transaction isolation: using a command log or copy-on-write for atomicity and rollback.
  • Snapshot strategies: full serialization vs. persistent data structures (e.g., immutable maps).
  • Code reuse: how each level extends the previous without rewriting core logic.
  • Trade-offs: memory vs. speed, consistency vs. availability, and complexity of concurrency.

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