This role builds and runs a shared knowledge layer that both employees and AI agents can rely on. The work mixes designing how information is organized, setting up connections to tools like Slack, Gong, Drive, and Notion, and teaching non-technical teams to keep their own content tidy. A strong candidate has run a knowledge or content program at scale, is comfortable with SaaS tools and basic troubleshooting, and can work with IT, Security, and Legal on who gets access to what.
How it fits the AI era
AI agents are only as useful as the context they can draw on, so this role sits at the base of that. Tools and agents can ingest and search messy sources, but people still decide what counts as accurate, how knowledge is structured, and what is sensitive. Judgment, clear writing, and getting teams to adopt good habits stay human work.
How it builds AI experience
The role offers hands-on time with an agent context platform and with the way AI agents pull from company knowledge, at a company that builds AI automation tools. Someone could prepare by trying n8n, reading up on Model Context Protocol, and building a small searchable knowledge base from sample documents with clear structure and labels.
Worth showing
- Taxonomy and content standards design
- Knowledge base or wiki program
- Training non-technical contributors
- SaaS integrations and troubleshooting
- Working with Security and Legal
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
About N8n
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Internal Context Engineer in Berlin Arbeitgeber: present of AI
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