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

SeniorPrefer not to say
May 2026Remote

Summary

System design round at OpenAI for a software engineer role, two interviewers, focused on a payment processing system. The question had a lot of surface area and I ran out of time on the part that mattered most.

Questions Asked (1)

Q1

Design a payment system that handles purchase requests, approval states, and batch settlement at midnight by generating a large file of all transactions from the day.

System DesignTechnical Trade-offsData Modeling
Author's notes

Spent way too long on the API and DB layers and basically ran out of runway before getting to the file generation piece, which was clearly the whole point.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design the data model and state machine for purchase requests and approvals. Describe the batch settlement process, focusing on reliability, idempotency, and performance. Discuss trade-offs and potential bottlenecks.

Pro tip: Emphasize idempotency and exactly-once processing in the batch job, as payment systems must handle retries and failures gracefully. Also, consider using a distributed lock or leader election to ensure only one settlement job runs at midnight.

1. Clarify Requirements

Ask about scale (transactions per day, peak load), consistency requirements, and failure handling. Understand the approval workflow and settlement file format.

2. Design Data Model

Define entities: PurchaseRequest, Approval, Transaction, SettlementBatch. Choose a database (SQL for ACID) and design schemas with appropriate indexes.

3. Design APIs and State Machine

Outline REST endpoints for creating requests, approving/rejecting, and querying status. Define state transitions (e.g., PENDING, APPROVED, REJECTED, SETTLED).

4. Design Batch Settlement

Describe how to generate the settlement file at midnight: query all approved transactions from the day, format them, and write to a file (e.g., CSV). Ensure idempotency and handle failures with retries.

5. Address Scalability and Reliability

Discuss partitioning, read replicas, asynchronous processing, and monitoring. Consider using a job scheduler (e.g., cron) and a distributed lock to prevent duplicate runs.

Key Points to Mention

  • Idempotency of settlement job to avoid duplicate transactions
  • Database choice: SQL for ACID vs NoSQL for scale
  • State machine for approval workflow with clear transitions
  • Batch processing performance: streaming vs loading all into memory
  • Failure handling: retries, dead-letter queues, and alerting
  • Security and compliance: encryption, audit logs, PCI DSS

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