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The Developer Evangelist will represent LlamaParse at events, demo products, create technical content, and engage with the developer community to promote document parsing solutions.

Represent and evangelize LlamaParse through conferences, meetups, demos, social media, and technical content. Build demos and example apps, create video and written walkthroughs, collaborate with product and engineering on launches, and gather developer feedback to drive adoption.

As a Lead Product Manager, you'll define product vision, manage product lifecycles, engage with users, set KPIs, and collaborate across teams to shape innovative AI-driven tools.

Run full-cycle enterprise sales into AI-native software companies by executing targeted outbound, building bottoms-up champions, converting product usage into pipeline, owning technical evaluations/POCs, and expanding accounts. Maintain CRM hygiene, forecast reliably, and use AI tools to accelerate research and outreach.

Generate qualified meetings and pipeline for AEs via inbound MQLs, PQLs, targeted outbound, and events. Research accounts, target technical and business buyers, craft personalized outreach, keep CRM updated, hit weekly meeting and pipeline targets, and use AI tools to accelerate prospecting.

As a Technical Recruiter at LlamaIndex, you will manage the full recruiting lifecycle focusing on technical roles, leveraging AI tools, and enhancing candidate experience while working closely with hiring managers.

Open call for candidates to submit speculative applications to join LlamaIndex and help shape AI and document-understanding narratives. Company will keep applicants in mind for future roles and considers applicants with arrest and conviction records per San Francisco ordinance.

The Mid-Market Account Executive is responsible for managing the sales cycle to close deals with companies under 500 employees, develop pipeline, and achieve revenue targets by working with various stakeholders and using AI tools.

The Enterprise Account Executive will drive customer acquisition and revenue growth by managing the full sales cycle, building relationships, and collaborating with technical teams to close deals with global enterprises.

Build and maintain benchmarks and evaluation frameworks for document understanding, run experiments, produce weekly technical content (blogs, reports, tutorials), publish analyses comparing models, contribute open-source examples and notebooks, and collaborate with ML teams to highlight capabilities and surface improvements.