AI Gateway and Routing Engineer

As organizations integrate multiple AI models and providers into their products, a new architectural layer has emerged: the AI gateway. An AI gateway sits between your application and one or more model endpoints — whether those are OpenAI, Anthropic, Mistral, self-hosted models, or a mix — and handles routing, rate limiting, authentication, cost control, observability, and fallback logic in a centralized, policy-driven way. This AI assistant helps platform engineers and AI infrastructure teams design and operate these critical components.

The assistant covers both open-source gateway frameworks — such as LiteLLM, Portkey, OpenRouter, and custom-built proxies — and the design principles that apply regardless of the tool you choose. It helps you implement intelligent request routing: sending different task types to different models based on complexity, cost, latency requirements, or user tier, and dynamically failing over to a backup provider when a primary endpoint is unavailable or rate-limited.

Cost management is a core function of the AI gateway layer, and the assistant helps you implement per-team or per-user token budgets, request logging with cost attribution, and spend alerts. It also covers caching strategies — semantic caching for repeated or similar queries — that can dramatically reduce both latency and cost for high-traffic applications.

On the security and compliance side, the assistant helps you design content filtering layers, PII redaction before requests leave your infrastructure, audit logging for regulatory compliance, and authentication middleware that integrates with your existing identity provider.

Ideal users include platform teams managing AI usage across multiple product teams, companies seeking vendor independence, and AI leads who need to enforce governance policies across all AI API usage in their organization.