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

SeniorPrefer not to say
Jun 2026Remote

Summary

System design round at Decagon for a software engineer role, focused entirely on building an AI Gateway service. The question had a lot of moving parts and the interviewer kept pushing on specific subsystems rather than letting me stay high-level.

Questions Asked (1)

Q1

Design an AI Gateway service that sits between internal application services and external model providers like OpenAI, Anthropic, and Google. How would you handle routing, rate limiting, observability, and resilience?

System DesignTechnical Trade-offsAPI & Integrations
Author's notes

This felt manageable at first and then the follow-ups kept coming.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then walk through the core components of the gateway: routing, rate limiting, observability, and resilience. For each, explain your design choices, trade-offs, and how they integrate to provide a reliable, scalable service.

Pro tip: Emphasize idempotency and graceful degradation: show how you prevent duplicate charges or side effects when retrying, and how the gateway can fall back to cheaper models or cached responses during provider outages.

1. Clarify Requirements and Constraints

Ask about expected QPS, latency SLOs, cost sensitivity, compliance needs, and whether the gateway should support streaming or batch. This ensures your design addresses the right priorities.

2. Design Routing and Load Balancing

Explain how to route requests based on model type, cost, latency, or provider health. Include dynamic provider selection, fallback chains, and A/B testing capabilities.

3. Implement Rate Limiting and Quotas

Describe per-user, per-team, and global rate limiting using algorithms like token bucket or sliding window. Discuss distributed rate limiting with Redis and how to handle bursts.

4. Ensure Observability

Cover logging, metrics, and tracing for each request, including provider latency, error rates, token usage, and cost. Mention tools like Prometheus, Grafana, and OpenTelemetry.

5. Build Resilience

Discuss retries with exponential backoff and jitter, circuit breakers, timeouts, and fallback strategies. Highlight idempotency keys to avoid duplicate side effects.

Key Points to Mention

  • Dynamic routing based on provider health, cost, and latency
  • Distributed rate limiting with Redis and token bucket algorithm
  • End-to-end tracing and metrics for debugging and cost tracking
  • Circuit breakers and fallback to secondary providers or cached responses
  • Idempotency keys to ensure safe retries
  • Caching strategies for repeated queries to reduce cost and latency

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