Building an Internal LLM Gateway / AI Proxy (EXPLAINED)
Hard project question on LLM gateway — auth, routing, rate limits, logging, key management, and multi-provider abstraction.
TL;DR — Quick Answer
An LLM gateway centralizes access to OpenAI/Bedrock/Anthropic/local models: SSO auth, API key vault, per-team quotas and budgets, request/response logging (PII-aware), routing and fallback, retry/idempotency (llm-024), prompt template registry, eval hooks, content moderation, audit trail, and unified OpenAI-compatible API for app teams. Benefits: security, cost control, vendor swap without app rewrites, compliance retention policies, and golden path for guardrails applied once org-wide.
The Interview Question
Design an internal LLM gateway (AI proxy) for your organization. What capabilities should it provide?
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GatewayProxyPlatformSecurityMulti-ProviderMicrosoftAmazonStripeOpenAI