What Youll Be Doing:
Design and maintain the external documentation system: API references, integration guides, onboarding flows, and troubleshooting content – treating it as a living product with real users and measurable outcomes.
Define AI-augmented documentation workflows: where LLMs assist with drafting, where they validate accuracy, and where human judgment is irreplaceable.
Work directly with engineers, PMs, and researchers to extract knowledge: you interview, synthesize, and structure what others know but haven't written down.
Own content quality signals: broken links, outdated docs, low-rated articles, search dead-ends. You set up the loops that catch decay before customers do.
Contribute to the information architecture: taxonomy, versioning strategy, content type standards, and the toolchain that supports them.
Lead content localization efforts, including multilingual adaptations, knowledge base structuring, and format alignment.
Manage the creation and distribution of release notes in collaboration with Product and R&D teams.
Contribute to building and stewarding the internal knowledge base for our own employees: capturing decision logs, architecture notes, research summaries, and runbooks so institutional knowledge doesn't live only in people's heads.
Comfortable reading code, API specs, and architecture diagrams: not necessarily writing production code, but enough to work as a credible peer to engineers.
Understands developer experience (DX) and user experience (UX) as a discipline: knows what makes technical, operational, and similar docs actually usable.
Uses LLMs as a force multiplier: for first drafts, translation, summarization, and doc-from-code generation, while knowing when output needs expert review.
Has hands-on experience with at least one AI-assisted docs workflow (e.g., GPT, Confluence, Claude, Notion, custom RAG on internal wikis or similar).
Think critically about AI-generated content: hallucination risk, freshness, attribution, and user trust.
Passion for knowledge management and sharing.
Experience in technical writing, knowledge management, or a similar role.
Experience in multi-disciplinary content creation and management within a B2B SaaS company.
Strong attention to detail with the ability to manage multiple projects simultaneously.
Excellent interpersonal and communication skills, with the ability to collaborate across teams.
Native-level English proficiency is required; proficiency in additional languages is an advantage.
A bachelors degree in a related field is an advantage.
Tools & ecosystem (nice to have, not a checklist): Docs platforms: Confluence, Document360, GitBook, Notion. AI tooling: Claude, Copilot, OpenAI, Cursor, custom LLM pipelines, prompt engineering for structured output. Spec formats: OpenAPI / Swagger, AsyncAPI, GraphQL schema docs.
