Documentation Engineer - Arize AI

The Opportunity

AI is rapidly transforming the world. Whether it's developing the next generation of human-level intelligence, enhancing voice assistants, or enabling researchers to analyze genetic markers at scale, AI is increasingly integrated into various aspects of our daily lives.

Arize AI is the leading AI observability and evaluation platform, empowering AI engineers to build and deploy high-performing, reliable models. As the AI landscape shifts from traditional ML to generative AI and agentic systems, Arize ensures teams have the tools to monitor, troubleshoot, and improve AI in production.

Our developer relations team's mission is to provide the best possible developer experience for our flagship products, Arize AX and Arize Phoenix. This role owns the documentation half of that mission: keeping our own docs accurate as the products change, expanding our guides and cookbooks so a developer can get from first read to working code without asking anyone for help, and making sure Arize is documented correctly in other people's material too, from integration partners to online courses.

Documentation now has two audiences reading it simultaneously: developers, and the coding agents working on their behalf. The same page has to be skimmable by a human and unambiguous to an agent that will act on it, and nobody in the industry has settled on how to do both well. That’s an exciting problem and it will be central to this role.

We are not looking for someone to hand-edit pages forever. We are heavy users of AI-driven automation and expect you to build systems that spot stale content, catch drift between the code and the docs, draft updates for review, and check that our examples still run. Good writing and editing skills are of course required for this role, but we expect you to use AI to greatly accelerate and amplify your skill.

Primary responsibilities:

• Own the health of Arize's product documentation: keep it accurate as we ship, and rewrite the parts that have stopped making sense
• Build automated systems that monitor documentation quality, detect drift between docs and code, test that code samples still work, and draft updates for human review
• Make our documentation work for coding agents as well as humans: structured content, machine-readable indexes, and real measurement of whether an agent can complete a task using our docs alone
• Write and refresh tutorials, cookbooks and open-source demonstration repositories that take a developer from introduction to value quickly
• Get Arize documented accurately outside our own site, working with integration partners, framework maintainers, and course and curriculum authors
• Create a stellar onboarding experience for new users, judged by whether they get to their first working eval unassisted