Startups · AI

AI Engineer

LiteLLM · San Francisco · On-site

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About LiteLLM

LiteLLM is the open-source AI gateway that puts your full AI stack behind one OpenAI-compatible key. Track and cap LLM spend, route to the right model, and self-host anywhere — even air-gapped. 140+ providers, 1,892 models. Backed by Y Combinator.

About the role

As the AI 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:

More about this role

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.

Skills: Python, LLM APIs, FastAPI

As the AI 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

The tech stack includes Python, FastAPI, Redis, Postgres.

1-2 years of...

Read the full posting on LiteLLM's site ↗

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