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

Senior
May 2026

Summary

System design round at OpenAI for a software engineer role. One question, 60 minutes, entirely focused on designing a payment service with a very specific constraint around double-charging. The depth they expected was pretty serious.

Questions Asked (1)

Q1

Design a payment service that sits between a point-of-sale machine and a downstream banking system, handling the full authorize-and-capture flow. The core constraint: a user must never be charged twice, even if the network drops mid-request or the POS retries the operation multiple times.

System DesignTechnical Trade-offsAPI & Integrations
Author's notes

This felt manageable at first and then quietly became a lot.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and constraints, then propose an idempotent API design with a unique transaction ID generated by the POS. Walk through the authorize-and-capture flow, emphasizing how idempotency keys and a durable transaction log prevent double charges, and discuss trade-offs around consistency, latency, and failure handling.

Pro tip: Emphasize that idempotency must be enforced at the server side with a persistent store, and that the POS should generate a unique idempotency key per transaction attempt. Also, mention that you would handle partial failures by making the capture operation idempotent as well, and use a state machine to track transaction status.

1. Clarify requirements and constraints

Ask about expected throughput, latency requirements, consistency guarantees, and failure scenarios. Confirm that the POS can generate unique transaction IDs and that the downstream banking system supports idempotent operations.

2. Design idempotent API

Define an API where each request includes a client-generated idempotency key (e.g., transaction ID). The server stores the key and the response, so repeated requests with the same key return the same result without re-executing the operation.

3. Outline authorize-and-capture flow

Describe the two-phase flow: first authorize (reserve funds), then capture (transfer funds). Ensure both phases are idempotent and that the transaction state is persisted atomically to avoid inconsistencies.

4. Handle failures and retries

Explain how the system handles network drops and retries: the POS retries with the same idempotency key, the server checks the key, and if the transaction is already processed, returns the stored response. Use timeouts and retries with exponential backoff.

5. Discuss trade-offs and scaling

Address trade-offs: strong consistency vs. availability, latency of synchronous calls, and storage overhead for idempotency keys. Mention scaling strategies like sharding by transaction ID and using a distributed cache for idempotency keys.

Key Points to Mention

  • Idempotency keys generated by the POS and enforced server-side with a persistent store.
  • Two-phase commit or state machine to track transaction status (authorized, captured, failed).
  • Exactly-once semantics achieved through idempotent operations and deduplication.
  • Handling of network partitions and retries with exponential backoff and timeouts.
  • Trade-offs between consistency, availability, and latency (CAP theorem).
  • Monitoring and alerting for duplicate charge attempts and reconciliation with the banking system.

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