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

SeniorPrefer not to say

May 2026

Summary

Airtable system design round focused entirely on async API patterns. One big meaty question, no warmup, just straight into the architecture discussion for the whole session.

Questions Asked (1)

Design an asynchronous API endpoint that accepts a request, returns immediately with a job ID, and processes the work in the background. The system must be idempotent so repeated calls with the same key don't duplicate side effects. Walk through the full request lifecycle including queueing, worker processing, status polling, client retries, failure handling, and cleanup.

System DesignAPI & IntegrationsTechnical Trade-offs

Author's notes

This one took me a while to even fully parse.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then walk through the full lifecycle from request to cleanup, emphasizing idempotency and failure handling. Use a concrete design with specific components (API gateway, queue, worker, database) and discuss trade-offs at each stage.

Pro tip: Demonstrate maturity by discussing how to handle partial failures and exactly-once semantics, and mention monitoring and alerting for stuck jobs. Also, tie your design to Airtable's use case of long-running operations like imports or exports.

1. Clarify Requirements and Constraints

Ask about expected throughput, latency SLAs, idempotency key scope, and failure recovery guarantees. Confirm whether the API should be RESTful or event-driven.

2. Design the Request Lifecycle

Outline the synchronous part: validate request, check idempotency key, enqueue job, return 202 with job ID. Discuss idempotency key storage and deduplication logic.

3. Detail Background Processing

Describe the queue (e.g., SQS, RabbitMQ), worker pool, job execution, and status updates. Cover retries, dead-letter queues, and idempotent side effects.

4. Explain Status Polling and Client Retries

Design a status endpoint that returns job state (pending, running, succeeded, failed). Discuss client retry strategies with exponential backoff and how to handle duplicate submissions.

5. Address Failure Handling and Cleanup

Cover failure scenarios (worker crash, queue outage), retry policies, and cleanup of old jobs and idempotency keys. Mention monitoring and alerting.

Key Points to Mention

Idempotency key storage with TTL and atomic check-and-set to prevent duplicate jobs
Queue selection (e.g., SQS, Kafka) and trade-offs between at-least-once vs exactly-once delivery
Worker design: concurrency, retries with exponential backoff, and dead-letter queue for poison messages
Status endpoint design: polling vs webhooks, and how to handle long-polling or server-sent events
Failure handling: idempotent side effects, transactional outbox pattern, and compensating actions
Cleanup: TTL for job records and idempotency keys, and archival of completed jobs

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