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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.
You will own the architecture and governance of DocPlanner's product knowledge infrastructure. This is a foundational role with significant scope and autonomy—you will define how product knowledge is structured, maintained, and distributed across the organization.
Key responsibilities:
**Structure & Content Model**: 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). Design a unified structure that serves both internal AI assistants (Kraken for customers, Noa for doctors) to eliminate duplicate maintenance.
**Code-to-Knowledge Pipeline**: Work directly in GitHub with read access to the monorepo. Extract feature logic and rules from code, translate them into clear, reviewable output. Continuously improve automation so fewer facts require manual confirmation. Enforce the rule that all new/changed features are generated from code from day one; older content is only refreshed when releases touch it or when it ranks among the most-used topics.
**Knowledge Base Migration**: Audit the current internal knowledge base article-by-article. Decide the fate of each: migrate to new structure, rewrite, replace with code-generated output, or archive. Propose a prioritized work plan based on usage frequency and change velocity. Lead the team through execution—you set method, explain it, review results, and maintain quality consistency across markets.
**Team Enablement & Skill Building**: Transition the team from writing articles to validating facts. Create working guides, examples, and training sessions. Build skills in writing self-contained facts, reviewing generated content, spotting knowledge gaps, working with repository-based content, and testing AI assistant answers. Be the go-to expert when the team is uncertain.
**Non-Code Knowledge**: Identify knowledge types the code doesn't contain (market differences, plan variations, 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, preparing facts in formats non-technical stakeholders can quickly confirm or reject.
**Knowledge Freshness**: Define the update cadence for dozens of monthly releases. Establish triggers, alerts, and SLAs for changes. Notify the Help Center team when releases invalidate published content, with precision so they can fix without re-reading entire articles.
**Cross-Functional Collaboration**: Partner with Product Experts (who feed and test the knowledge base), Help Center (who publish customer-facing content), AI assistant owners (Kraken/Noa), and Engineering (for repository access and code changes needed to enable 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.
Essential skills and experience:
- Comfortable with Git and GitHub: branches, pull requests, reading diffs, navigating large unfamiliar codebases, reading code to understand rules and edge cases. (You do not need to be a software engineer, but you must be able to explore a repository independently.)
- Proven experience designing content structures: small self-contained content pieces, labels, metadata, and standards you defined and enforced across teams.
- Experience with documentation living in repositories: versioned, reviewed, and built like code (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 answers empirically.
- Demonstrated ability to get busy experts to review facts quickly and design formats that enable fast validation.
- Experience teaching teams new workflows and making them stick (guides, examples, training sessions, patience).
- Independence to build a novel role with no precedent: define scope, defend boundaries, and surface risks early.
- Professional English (written and spoken). Additional languages a plus: Spanish, Portuguese, Polish, Italian.
Note: Visa sponsorship is not available; you must have legal right to work in your country of residence or the role location.
