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

Senior
Apr 2026Remote

Summary

Did a virtual onsite system design round at OpenAI for a software engineer role, focused entirely on payment system design. Pretty intense scope for a single session.

Questions Asked (1)

Q1

Design a payment system from scratch.

System DesignTechnical Trade-offsData Modeling
Author's notes

There's a lot of surface area here and I think I spread myself too thin early on.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements (functional and non-functional) and scale, then propose a high-level architecture covering core components like payment processing, ledger, and integrations. Dive into critical areas such as idempotency, consistency, and security, and discuss trade-offs for each design decision.

Pro tip: Emphasize idempotency and exactly-once processing early, as payment systems must handle retries and network failures without double-charging. Also, mention the importance of reconciliation with external providers to ensure data integrity.

1. Clarify Requirements

Ask about functional requirements (payment methods, currencies, refunds) and non-functional requirements (scale, latency, consistency, compliance). Establish scope and constraints.

2. High-Level Design

Outline main components: API gateway, payment service, ledger, database, message queue, and external integrations (banks, card networks). Sketch data flow for a payment transaction.

3. Deep Dive into Critical Areas

Discuss idempotency, consistency (ACID vs BASE), data modeling (transactions, accounts), and security (PCI DSS, encryption). Explain how to handle failures and retries.

4. Scalability and Reliability

Address horizontal scaling, partitioning, replication, and fault tolerance. Discuss monitoring, alerting, and disaster recovery.

5. Trade-offs and Wrap-up

Summarize key trade-offs (e.g., consistency vs availability, SQL vs NoSQL) and justify choices. Mention potential future improvements.

Key Points to Mention

  • Idempotency keys to prevent duplicate payments
  • Double-entry bookkeeping for accurate ledger and auditing
  • Exactly-once processing semantics using message queues and deduplication
  • PCI DSS compliance and tokenization for card data
  • Database sharding and replication for scalability and high availability
  • Reconciliation with external payment providers to resolve discrepancies

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