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

SeniorPrefer not to say
May 2026

Summary

System design round at Roblox for a software engineer role. The question was all about scheduled payments, which sounds straightforward until you actually have to think through the full reliability story.

Questions Asked (1)

Q1

Design a payment system that supports scheduled (delayed) payments, where users can set a payment to execute at a future time. Address persistent storage, reliable triggering, idempotency, retry behavior on transient failures, exactly-once execution guarantees, and consistency vs latency trade-offs at scale.

System DesignTechnical Trade-offsAPI & Integrations
Author's notes

This one had a lot of surface area and I think I spread myself too thin early on.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design a durable scheduler that persists payments and triggers them reliably, using idempotent execution and retries with backoff. Discuss trade-offs between consistency and latency, and explain how to achieve exactly-once semantics via deduplication and transactional outbox patterns.

Pro tip: Emphasize that exactly-once execution is achieved through idempotent operations and deduplication, not by trying to prevent duplicate deliveries. Also, mention that you'd monitor the lag between scheduled and actual execution times as a key SLI.

1. Clarify Requirements and Scale

Ask about expected volume, payment types, latency tolerance, and consistency needs. Establish SLAs for execution time and failure handling.

2. Design Persistent Storage and Scheduler

Choose a durable store (e.g., SQL with time-based indexes) for scheduled payments. Implement a scheduler that polls or uses a timing service (e.g., cron, delay queues) to trigger due payments.

3. Ensure Reliable Triggering and Idempotency

Use a message queue or event stream to decouple scheduling from execution. Make payment execution idempotent by using unique transaction IDs and deduplication tables.

4. Handle Retries and Exactly-Once Execution

Implement retries with exponential backoff for transient failures. Achieve exactly-once by combining idempotent operations with transactional outbox and deduplication.

5. Discuss Consistency vs Latency Trade-offs

Explain how to balance strong consistency (e.g., for payment state) with low latency (e.g., for scheduling). Consider partitioning, sharding, and eventual consistency where appropriate.

Key Points to Mention

  • Use a durable, time-indexed store (e.g., SQL with an index on scheduled_time) for persistence.
  • Leverage a distributed scheduler (e.g., Quartz, Kubernetes CronJobs) or a delay queue (e.g., RabbitMQ delayed messages, SQS delay queues) for reliable triggering.
  • Ensure idempotency by assigning a unique idempotency key to each payment and checking a deduplication store before execution.
  • Implement retries with exponential backoff and jitter, and use a dead-letter queue for persistent failures.
  • Achieve exactly-once execution by combining idempotent operations with a transactional outbox pattern to atomically update state and publish events.
  • Trade-offs: Strong consistency for payment state may increase latency; use asynchronous processing and eventual consistency for non-critical parts to scale.

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