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n8n is an open workflow orchestration platform built for the AI era, enabling technical teams to automate faster with the freedom of code and speed of no-code. The company has grown to 260+ employees across Europe and the US, with 650,000+ active developers in its community, 190K+ GitHub stars, and a $5.2bn valuation backed by Sequoia and SAP.
As Internal Context Engineer, you will build and operate n8n's shared context infrastructure—the "company brain"—enabling both people and AI agents to reliably access accurate, well-structured, and appropriately governed knowledge across the organization.
Key responsibilities:
**Design Information Architecture**: Define taxonomy, structure, contributor guidelines, and templates that transform fragmented company knowledge into reliable, reusable context. Establish standards that make knowledge easy to navigate and maintain without creating duplication or content sprawl. Evolve standards as functions, knowledge sources, and agentic use cases grow.
**Onboard & Enable Teams**: Onboard functions to the company brain and train designated champions to structure and maintain their own knowledge. Provide non-technical contributors with guidance, templates, and support for high-quality independent contributions. Partner with the Internal AI Enablement Lead to develop a shared network of champions scaling knowledge practices across n8n.
**Operate Context Platform**: Configure and operate ingestion from qualitative sources (Slack, Gong, Drive, Notion) using the context platform's tooling. Own day-to-day platform configuration and basic troubleshooting, escalating engineering challenges to the Automation team or vendor. Partner with IT, Security, and Legal to define requirements for how people and AI agents access sensitive company knowledge.
**Build for Long-Term Trust & Reuse**: Keep content structures, contributor guidelines, and knowledge freshness current as n8n and the platform evolve. Work with functions to ensure the company brain becomes a trusted source of context. Provide product feedback to the context platform vendor and anticipate shared context patterns future agents will need.
**Requirements**
Must-haves:
- Proven experience designing structured content or knowledge programs at scale, including taxonomies, style guides, contributor guidelines, templates, or information architecture
- Hands-on experience with knowledge or context systems; understanding of turning fragmented qualitative information into reliable, reusable content
- Comfort configuring and operating SaaS knowledge or context platforms, working with APIs and integrations, and independently troubleshooting basic issues
- Track record training non-technical stakeholders and enabling them to confidently maintain high-quality content over the long term
- Comfort partnering with IT, Security, and Legal on access requirements and compliance-sensitive data flows
- Strong written and verbal communication skills; ability to set clear quality bars for structured, documented, and shared company knowledge
Nice-to-haves:
- Familiarity with Qontext.ai or comparable agent-context platforms
- Experience with or strong understanding of Model Context Protocol (MCP)
- Background in knowledge management, metadata, or data governance
