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Knowledge Architect and Product Enablement Expert

Docplanner·BrazilRemotesenior

In short

  • →Arquitecto del conocimiento productivo que estructura y mantiene información técnica a partir del código.
  • →Trabaja directamente en GitHub, convirtiendo lógica de features en hechos claros de conocimiento usable por asistentes de IA.
  • →Destacado: todos los nuevos cambios deben generar conocimiento desde el código desde el primer día.

B2+ (específico: capaz de entender documentación técnica y colaborar en inglés con equipos

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The questions they'll ask you

1. ¿Cómo identificarías las partes del código que contienen lógica crítica para un asistente de IA, y cómo las convertirías en un hecho verificable?

2. ¿Qué método usarías para convencer a un equipo resistente a dejar de escribir artículos y empezar a validar hechos generados por código?

3. ¿Cómo diseñarías un flujo para recopilar información no codificada (como diferencias entre mercados) que sea repetible y rápida para revisar?

🔒 +7 more questions

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💵 USD · Remote · No visa

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What they ask for

  • ✓Experiencia previa en conocimiento de producto o documentación técnica con enfoque en calidad y estructura
  • ✓Capacidad para leer y entender código en repositorios de monorepo (ej. JavaScript/TypeScript)
  • ✓Habilidad para convertir lógica de software en hechos claros, autocontenidos y verificables
  • ✓Experiencia en gestión de equipos de conocimiento o soporte con enfoque en escalabilidad
  • ✓Capacidad para enseñar procesos y guiar cambios de hábitos en equipo
  • ✓Capacidad para colaborar con Product Managers, Marketing y Expertos de producto

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

GitHubMonorepoJavaScriptTypeScriptAI assistants (Kraken, Noa)Content modelingKnowledge baseProduct documentationProduct taxonomyMetadata

Who should you write to at Docplanner?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

Company Description At Docplanner Group, we’re on a mission to help people live longer, healthier lives. As the world’s largest healthcare platform, each month, we connect 24 million patients with 280k doctors across 13 countries (through brands like ZnanyLekarz, Doctoralia, MioDottore, DoktorTakvimi, and jameda). Our marketplaces, SaaS and AI tools simplify daily tasks and help doctors, clinics and hospitals work more efficiently, so they can focus on what really matters: caring for their patients. Why join us? Real impact – We help doctors help patients. Your work truly makes a difference. At scale, yet agile – 3,000+ employees, but still fast, flexible, and hands-on. ✨ Shape the future, sustain growth – Make a difference now and build for long-term success. What you will own The structure of our product knowledge Define and keep the content model for Docplanner product knowledge : small self-contained facts, how topics are organised, which labels and metadata we use, and what belongs to the internal knowledge base versus the external one for customers and doctors. Set the quality standard. Every fact carries a reference to where it came from (repository, file, place in the code), so anyone can check it again later instead of trusting it blindly. Choose one structure that works for both assistants, Kraken for customers and Noa for doctors, so we do not end up maintaining the same knowledge twice. Getting knowledge out of the code Work directly in GitHub with read access to the monorepo and the other repositories. Find where the logic of a feature really lives , read it well enough to understand the rules and the special cases, and turn it into clear output that other people can review . Improve the way we generate this output, so that over time fewer facts need a person to confirm them. Simplifying is key . Protect one rule: every new or changed feature is generated from the code from day one. Older content is only redone when a release touches it, or when it is one of the most used topics in Kraken and in Customer Care. We are not going to rewrite the whole knowledge base in one big project. Our current internal knowledge base Review what we have today, article by article, and decide what happens to each part: move it to the new structure, rewrite it, replace it with output generated from the code, or archive it because it is no longer useful. Propose the order of that work, with clear reasons based on how much each topic is used and how often it changes, and agree with the manager of the team. Lead the team through that work. You do not do it alone. You decide the method, you explain it, you review the result, and you keep the quality consistent across markets and people . Teaching the team to work in the new way Bring the team from writing articles to checking facts . This is a real change in habits, and it needs to be taught. Create the working guides, examples and short training sessions that make the new way easy to follow, and update them as the method changes. Build new skills inside the team : how to write a small self-contained fact, how to review generated content, how to spot a knowledge gap, how to work with content that lives in a repository, and how to test an AI assistant's answers. Be the person the team asks when they are not sure . Answer, and then write the answer down so the next person does not have to ask. The facts that are not in the code Identify the types of knowledge that the code simply does not contain : differences between markets and plans, the wording on screen, what the patient sees, screenshots. For each type, design a way of getting that information that we can repeat every time, together with Product Managers, Product Marketing and Product Experts. Run the review loop with the people who own each feature. Prepare the facts in a format that a person without a technical background can confirm, correct or reject quickly.

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