Developer Advocate

Responsibilities

• Build runnable cookbooks, quickstarts, reference applications, and end-to-end tutorials for AI model inference and production use.
• Create rapid launch content for new models and techniques, including working demos, benchmarks, and practical usage guides.
• Establish repeatable workflows for model access, evaluation, and publishing.
• Publish and engage across documentation, blogs, examples, cookbooks, Discord, newsletters, GitHub, X, Reddit, YouTube, Hacker News, and relevant open-source projects.
• Answer developer questions publicly, contribute code, review pull requests, and turn recurring issues into durable content.
• Speak at conferences, lead workshops, mentor hackathons, and host developer events.
• Surface developer feedback and product friction to product and engineering teams using concrete evidence, then communicate fixes publicly.
• Measure adoption, activation, time to first successful build, content-driven signups, and event-driven developer outcomes.

Requirements

• 5+ years of combined engineering and developer-facing experience, with meaningful experience in both areas.
• Strong Python and working knowledge of TypeScript/JavaScript.
• Experience building and deploying applications and reviewing technical samples.
• Production experience with LLM APIs and at least one agent framework.
• Hands-on experience fine-tuning, evaluating, and deploying models.
• Understanding of inference latency, throughput, and cost drivers.
• Public technical communication track record through writing, talks, videos, open-source work, or an earned audience.
• Conference, meetup, or workshop speaking experience.
• Ability to rapidly learn new research and technologies and produce working implementations.
• Strong ownership, project-scoping, and execution skills.

Nice-to-haves

• Open-source contributions or maintainership in AI/ML, including inference engines, model libraries, agent frameworks, or evaluation tooling.
• Depth in inference optimization, serving architecture, post-training, or evaluation methodology.
• Experience establishing content operations, launch processes, event playbooks, or community programs.
• Video production experience.
• Relationships with AI research or open-model communities.
• Daily use of frontier coding agents.

Compensation

• Annual salary range: $200,000–$230,000.