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

SeniorPrefer not to say
Apr 2026

Summary

System design round at OpenAI for a software engineering role. The whole session was focused on payment infrastructure, which sounds straightforward until you get to reconciliation and partial failures and realize you've been handwaving over the hard parts your whole career.

Questions Asked (1)

Q1

Design a payment system covering the full flow: initiation, authorization, capture, refunds, and idempotency. Security is out of scope. Place particular emphasis on how you reconcile your internal ledger against an upstream payment processor, how you detect and resolve mismatches, batch vs streaming reconciliation approaches, and how you handle partial failures and disputes.

System DesignTechnical Trade-offsAPI & Integrations
Author's notes

I started with the happy path, which felt fine, but the interviewer kept steering toward reconciliation and I could feel myself getting vague.

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AI HintsAI Generated

Suggested Approach

Start by outlining the core payment flow and data model, emphasizing idempotency and state transitions. Then dive deep into reconciliation, comparing batch and streaming approaches, and detailing mismatch detection and resolution. Finally, address partial failures and disputes, showing how they integrate with the ledger and reconciliation.

Pro tip: Emphasize that reconciliation is not just about finding mismatches but also about automating resolution and learning from patterns to prevent future issues. Discuss how you'd design for observability and alerting on reconciliation metrics.

1. Define the Payment Flow and Data Model

Outline the end-to-end flow: initiation, authorization, capture, refunds, and idempotency. Describe the key entities (Payment, Transaction, LedgerEntry) and their state machines.

2. Design Idempotency and State Management

Explain how idempotency keys are used to prevent duplicate operations, and how state transitions are managed to handle retries and partial failures.

3. Implement Reconciliation: Batch vs Streaming

Compare batch (e.g., daily file drops) and streaming (e.g., webhooks, message queues) reconciliation. Discuss trade-offs in latency, complexity, and reliability.

4. Detect and Resolve Mismatches

Describe how to detect mismatches (e.g., missing transactions, amount discrepancies) and the resolution process (automated retries, manual investigation, adjustments).

5. Handle Partial Failures and Disputes

Explain how to manage partial failures (e.g., authorization succeeded but capture failed) and disputes (chargebacks), including ledger adjustments and communication with the processor.

Key Points to Mention

  • Idempotency keys and exactly-once processing semantics
  • Double-entry ledger for internal accounting and reconciliation
  • Batch reconciliation using settlement files vs streaming via webhooks/events
  • Mismatch detection: comparing internal ledger with processor reports, identifying missing/duplicate/amount mismatches
  • Automated resolution strategies: retries, compensating transactions, and manual escalation
  • Handling partial failures: state machine design, timeouts, and compensating actions
  • Dispute management: chargeback flow, evidence submission, and ledger impact

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