LiteLLM is the open-source AI gateway used by developers and enterprises to access, manage, and govern LLMs through a unified interface.

Teams use LiteLLM to route requests across model providers, control spend, monitor usage, implement security policies, and reliably operate AI applications in production.

We are looking for our first Developer Relations hire to help more developers discover LiteLLM, understand what they can build with it, and successfully deploy it in production.

Why We’re Hiring

LiteLLM has a large and growing technical community. Developers discover the project through GitHub, documentation, search, technical content, and recommendations from other engineers.

But discovering LiteLLM is only the beginning.

Developers need to quickly understand how LiteLLM fits into their stack, see credible examples of it solving real problems, and get from their first request to a production deployment. They also need clear ways to share feedback, contribute to the project, and learn about new capabilities.

You will help us build that developer journey.

This is LiteLLM’s first dedicated Developer Relations role. You will establish how we educate developers, engage with the community, support product launches, and turn developer feedback into better documentation, examples, and product decisions.

What This Job Actually Is

This is a hands-on technical individual-contributor role.

You will spend much of your time building with LiteLLM and turning what you learn into resources that help other developers succeed. You should be equally comfortable opening a code editor, explaining an infrastructure concept, and talking with developers about where they are getting stuck.

In a typical month, you will:

• Build and maintain runnable demos, sample applications, integrations, and reference architectures for real LiteLLM use cases.
• Create technical guides, videos, workshops, launch demos, and deep dives that make complex capabilities understandable and immediately usable.
• Engage directly with developers through GitHub, community channels, livestreams, meetups, conferences, and other technical forums.
• Partner with Product and Engineering on launches so new capabilities ship with strong examples, documentation, and a clear technical story.
• Identify recurring questions and points of friction, then turn them into better documentation, examples, product feedback, issues, or code contributions where appropriate.
• Explore the wider AI developer ecosystem and build useful examples with the models, frameworks, tools, and platforms LiteLLM users care about.
• Use developer feedback and adoption data to decide which educational resources, integrations, and community initiatives will have the greatest impact.
• Represent LiteLLM publicly through technical talks, workshops, videos, podcasts, and conversations with the developer community.

This is not a traditional social-media or event-marketing role, and it is not a frontline support position.

You will help individual developers, but the goal is to turn what you learn into resources and improvements that help the entire community. You will not be measured by content volume or impressions alone. The best outcome might be a runnable example that unlocks an important use case, an explanation that becomes the canonical resource for a difficult topic, or a pattern of feedback that leads us to improve the product.

Because this is