AI Engineer

LiteLLM•San Francisco, CA

About The Position

LiteLLM is the world's most popular AI Gateway, trusted by companies like Adobe, Netflix, and NASA. We're building the next generation of infrastructure for AI applications—and now we're building our second product. As the Backend LLM Engineer, you'll be responsible for ensuring LiteLLM unifies the format for calling LLM APIs in the broader OpenAI + Anthropic spec. This involves writing transformations to convert API requests from OpenAI/Anthropic spec to various LLM provider formats, building provider-agnostic unification functionality (e.g. session management across non-openai models for /v1/responses API, etc.). You'll work directly with the CEO and CTO on critical projects including: System design for supporting provider level features at the gateway level (skills, compaction, batches, etc.). Thinking about the developer experience - to support millions of users who leverage your work via LiteLLM's Python SDK. Building across LLM's, MCP's, and Agents by maintaining an excellent LLM interoperability layer, supporting a wide range of MCP Auth flows and enabling various Agent use-cases.

Requirements

Python
LLM APIs
FastAPI
1-2 years of backend/full-stack experience with production systems
Experience working with the OpenAI api (understand the difference between /chat/completions and /responses, and can speak to API-specific nuances)
Strong work ethic and ability to thrive in small teams
Eagerness to talk to users and help solve real problems

Nice To Haves

Passion for open source and user engagement

Responsibilities

Ensuring LiteLLM unifies the format for calling LLM APIs in the broader OpenAI + Anthropic spec.
Writing transformations to convert API requests from OpenAI/Anthropic spec to various LLM provider formats.
Building provider-agnostic unification functionality (e.g. session management across non-openai models for /v1/responses API, etc.).
System design for supporting provider level features at the gateway level (skills, compaction, batches, etc.).
Thinking about the developer experience - to support millions of users who leverage your work via LiteLLM's Python SDK.
Building across LLM's, MCP's, and Agents by maintaining an excellent LLM interoperability layer, supporting a wide range of MCP Auth flows and enabling various Agent use-cases.