Developer Evangelist, Technical Content

Join us and help shape the future of AI by defining the narrative around document understanding.

ABOUT LLAMAINDEX

LlamaIndex builds LlamaParse, the world's best agentic OCR and document parsing engine for AI applications. Enterprises and developers use LlamaParse to turn their hardest documents, including dense PDFs, scanned files, tables, and forms, into clean structured data their AI systems can actually use, at a scale of millions of pages a day. Document ingestion is one of the most underestimated problems in AI, and LlamaParse is how teams solve it.

ABOUT THE ROLE

We're looking for a Developer Advocate to be the public face of LlamaParse, out in the world in front of real developers and real teams, showing what the product can do.

This is a role for someone who does their best work in person and on camera. You'll spend your time at events, running demos, and posting on social media, and you'll evangelize the product by showing it in action: real documents going in, real structured data coming out. The most convincing thing you can do is share concrete, lived experience that makes developers want to try LlamaParse themselves.

We see this as an open-level role. We care far more about how compelling you are in a room and how well you can demo a product than about years on a résumé.

WHAT YOU'LL DO

• Get out into the world. Represent LlamaParse at conferences, meetups, hackathons, and workshops by speaking, demoing live, and meeting developers and teams face to face. This is the core of the job.

• Evangelize the product through real experiences. Walk through actual document-parsing problems, show LlamaParse handling messy real-world files, and tell the stories of how teams use it in production.

• Be highly active and visible on social media, including X, LinkedIn, and YouTube. Post demos, before-and-after parsing examples, launch content, and threads that show developers what LlamaParse does.

• Create technical content across formats, including video walkthroughs, livestreams, blog posts, and conference talks, all centered on LlamaParse and the document-ingestion problem.