Own documentation systems and AI-augmented workflows for a scientific data and AI platform. Build and maintain docs-as-code pipelines, LLM-backed authoring tools, and content optimized for AI agent consumption.
Salary not listed
Remote5+ YOETechnical Writing
About the role
Responsibilities
Own the documentation site and its publishing as software: the docs-as-code repo, the CI/CD publishing pipelines, build performance, and automated link, structure, and quality checks.
Build and grow AI-augmented documentation workflows: AI-assisted drafting, summarization, classification, consistency and staleness checks, and a feedback loop that improves generation quality over time, all with human oversight.
Build docs-as-AI-agents position: structure and transform content so AI systems can reliably chunk, index, and reason over it, and stand up and maintain MCP-style interfaces so agents and assistants consume our docs accurately.
Generate reference documentation from source (OpenAPI and related specs) and keep docs in lockstep with the platform as code changes.
Lower the barrier for internal contributors (PMs, squad leads, engineers) to ship their own docs through the docs-as-code workflow, and reduce repetitive work through automation.
Own the release-notes and customer-communications cadence that goes out with every platform release, and run the SME review that keeps it accurate and on time.
Own the documentation style guide, hold the review-and-publish gate, and keep the team runbook current so the function is not dependent on any one person.
Requirements
5+ years owning documentation tooling, content engineering, or developer documentation for a developer-platform or enterprise B2B product.
Engineering ability in a scripting or web stack (for example Python, TypeScript, or JavaScript) and real fluency with docs-as-code: Git, pull-request review, CI/CD, and a static-site or CMS publishing pipeline.
Hands-on experience building AI-augmented or LLM-backed workflows: integrating LLM APIs, AI-assisted authoring, and structuring content for AI consumption.
Ability to read and reason about a real codebase and API surface well enough to document it accurately and to build tooling against it.
Strong editorial judgment: you can take a dense engineering change and make it clear, correct, and customer-safe.
Bachelors or Masters degree in a technical field, or equivalent practical experience.
Nice-to-Haves
Experience making documentation consumable by AI agents (llms.txt, content negotiation, RAG pipelines, MCP servers).
Experience in BioPharma or scientific software, or in regulated and validated (GxP) environments.
Experience generating reference docs from OpenAPI or related specifications with two-way Git sync.
Developer-relations or developer-education exposure.
Skills
PythonTypeScriptJavaScriptGitCI/CDDocs-As-CodeLLM APIsRag PipelinesOpenapiStatic Site Generators
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