Openai·Software Engineer·Technical Phone Screen·Senior

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Jun 2026Remote

Summary

Got a coding problem for an OpenAI SWE round that was basically a mini ledger system for GPU credits. The core challenge was getting the expiry logic and FIFO-by-expiration deduction right under constraints that made brute force a bit risky.

Questions Asked (1)

Design and implement a GPU credit ledger that supports creating grants with expiration times, subtracting credits (consuming from earliest-expiring grants first), and querying the current balance while ignoring expired grants.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

The problem sounds clean on paper but the edge cases stack up fast.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a data structure like a min-heap keyed by expiration time to efficiently consume from earliest-expiring grants. Discuss lazy deletion of expired grants during balance queries and consumption, and analyze time/space complexity while considering trade-offs for different scales.

Pro tip: Mention that you would use a min-heap for efficient consumption and a separate variable for total balance, but also discuss how to handle expired grants lazily to avoid O(n) cleanup on every operation. This shows you think about real-world performance and edge cases.

1. Clarify Requirements and Constraints

Ask about expected scale (number of grants, operations per second), whether expiration times are known in advance, and if concurrent access is needed. This determines the choice of data structures and synchronization.

2. Design Data Structures

Propose a min-heap (priority queue) keyed by expiration time to track grants, and maintain a running total of non-expired credits. Consider using a hash map for quick grant lookup if needed for updates or deletions.

3. Implement Core Operations

For createGrant: add to heap and update total. For subtract: lazily remove expired grants from heap top, then consume from earliest-expiring grants, updating total. For getBalance: lazily remove expired grants and return total.

4. Analyze Complexity and Trade-offs

Discuss time complexity: O(log n) for insert, amortized O(log n) for subtract (due to lazy deletion), and O(1) for balance after cleanup. Compare with alternative approaches like sorted lists or balanced BSTs.

5. Address Edge Cases and Extensions

Cover scenarios like consuming more credits than available, grants expiring mid-operation, and potential concurrency issues. Suggest extensions like persistence or distributed ledger if relevant.

Key Points to Mention

Use a min-heap keyed by expiration time to efficiently access earliest-expiring grants.
Lazy deletion of expired grants to avoid O(n) cleanup on every operation.
Maintain a running total of non-expired credits for O(1) balance queries after cleanup.
Time complexity: O(log n) for grant creation and amortized O(log n) for consumption.
Trade-offs: heap vs. sorted list vs. balanced BST in terms of insertion, deletion, and query performance.
Edge cases: insufficient credits, simultaneous expiration and consumption, and thread safety.

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