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

SeniorPrefer not to say
Jun 2026

Summary

System design round at Nuro for a software engineering role. The whole session was basically one big webhook design question that kept expanding the more I answered, which was either fun or exhausting depending on how you look at it.

Questions Asked (1)

Q1

Design a webhook delivery system where clients register subscription endpoints and the system reliably sends event notifications via HTTP POST. Cover event ingestion, queueing, retries with backoff, idempotency, authentication, dead-letter queues, ordering vs throughput trade-offs, scaling delivery workers, and monitoring.

System DesignAPI & IntegrationsTechnical Trade-offs
Author's notes

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements (scale, latency, ordering guarantees, delivery semantics) and then walk through the end-to-end flow: event ingestion, durable queueing, delivery workers with retries and backoff, and dead-letter handling. Emphasize trade-offs (e.g., ordering vs throughput, at-least-once vs exactly-once) and how you'd monitor and scale the system.

Pro tip: Proactively discuss idempotency and how clients can deduplicate events, since webhook delivery is typically at-least-once; this shows you understand real-world reliability constraints. Also, mention that you'd provide a way for clients to verify webhook authenticity (e.g., HMAC signatures) and handle replay attacks.

1. Clarify Requirements and Constraints

Ask about expected event volume, latency requirements, ordering needs, and delivery guarantees (at-least-once vs exactly-once). This shapes the entire design.

2. Design Event Ingestion and Queueing

Describe how events enter the system (API, internal producers) and are durably queued (e.g., Kafka, SQS) with partitioning for scale and ordering.

3. Implement Delivery Workers with Retries and Backoff

Explain how workers consume events, attempt HTTP POST with timeouts, and retry with exponential backoff and jitter. Include idempotency keys and authentication (e.g., HMAC signatures).

4. Handle Failures and Dead-Letter Queues

After max retries, move events to a DLQ for manual inspection or alerting. Discuss how to replay DLQ events and avoid poison messages.

5. Scale, Monitor, and Trade-offs

Scale workers horizontally, monitor queue depth, delivery latency, success rates, and set up alerts. Discuss ordering vs throughput (e.g., per-endpoint ordering with partitioned queues) and other trade-offs.

Key Points to Mention

  • At-least-once delivery semantics and idempotency keys to allow client-side deduplication
  • Retry strategy with exponential backoff and jitter, plus circuit breakers to avoid overwhelming failing endpoints
  • Authentication and security: HMAC signatures, TLS, and secret rotation for webhook verification
  • Dead-letter queue (DLQ) for failed deliveries after max retries, with alerting and replay capabilities
  • Ordering vs throughput trade-off: per-endpoint ordering via partitioned queues vs parallel delivery for higher throughput
  • Monitoring and observability: metrics (success rate, latency, queue depth), logging, tracing, and alerting on anomalies

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