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DocPlanner Group is the world's largest healthcare platform, connecting 24 million patients with 280,000 doctors across 13 countries. The company operates multiple brands (ZnanyLekarz, Doctoralia, MioDottore, DoktorTakvimi, jameda) and provides marketplaces, SaaS, and AI tools to help healthcare professionals work more efficiently.
In this role, you will architect and own the product knowledge infrastructure for DocPlanner's ecosystem. Your responsibilities span five major areas:
**Knowledge Structure & Standards**: Define the content model for all product knowledge—how facts are organized, labeled, and stored. Establish quality standards requiring every fact to reference its source (code repository, file, location). Create a unified knowledge structure that serves multiple AI assistants (Kraken for customers, Noa for doctors) without duplication.
**Code-to-Knowledge Extraction**: Work directly in GitHub repositories with read access to the monorepo. Extract feature logic, rules, and edge cases from code and translate them into clear, reviewable documentation. Continuously improve automation so fewer facts require manual confirmation over time. Enforce the rule that all new or changed features generate documentation from code on day one.
**Knowledge Base Migration**: Audit the current internal knowledge base article-by-article. Decide the fate of each piece: migrate to new structure, rewrite, replace with code-generated content, or archive. Propose a prioritized work plan based on usage frequency and change velocity. Lead the team through this transition, maintaining quality consistency across markets.
**Team Enablement & Training**: Shift the team's mindset from writing articles to validating facts. Create working guides, examples, and training sessions. Build team skills in writing self-contained facts, reviewing generated content, identifying knowledge gaps, working with repository-based content, and testing AI assistant outputs. Serve as the go-to expert for methodology questions.
**Non-Code Knowledge Management**: Identify knowledge types the code doesn't contain (market differences, UI wording, patient-facing content, screenshots). Design repeatable processes with Product Managers, Product Marketing, and Product Experts to capture this information. Run review loops with feature owners, presenting facts in formats non-technical stakeholders can quickly validate or reject.
**Keeping Knowledge Current**: Define update triggers and ownership for dozens of monthly releases. Alert the Help Center team when releases invalidate published content, with precision so they can fix issues without re-reading entire articles.
**Cross-Functional Collaboration**: Partner with Product Experts (who feed and test the knowledge base), Help Center teams (who publish customer-facing content), AI assistant owners (who consume your output), and Engineering (for repository access and code changes needed to support knowledge extraction).
**Requirements**
- 4–7 years of professional experience in technical writing, documentation engineering, knowledge management, developer experience, solutions engineering, or comparable field with real ownership. This is not an entry-level role.
- Genuine comfort with Git and GitHub: branches, pull requests, reading diffs, navigating unfamiliar large codebases, and reading code well enough to understand rules and edge cases. Software engineering background not required; ability to independently explore repositories is.
- Experience designing content structures: small self-contained content pieces, labels, metadata, and standards you defined and enforced across teams. Daily use of Markdown, YAML, or JSON.
- Hands-on experience with documentation that lives in repositories: versioned, code-reviewed, and built like software (not document folders).
- Working understanding of how AI assistants consume content: retrieval mechanisms, why well-written articles can still produce poor answers, and how to test assistant outputs empirically.
- Proven track record getting busy experts to review facts quickly and designing formats that enable fast validation.
- Experience teaching teams new workflows and making them stick through guides, examples, training sessions, and patience.
- Independence to build a novel role with no precedent: you will define scope, defend boundaries, and surface risks early.
- Professional English (written and spoken). Additional languages a plus: Spanish, Portuguese, Polish, Italian.
