About CyberArk

CyberArk, a Palo Alto Networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. CyberArk’s AI-powered Identity Security Platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. With Identity Security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, IT, developers and machines, to securely access any resource, located anywhere, from everywhere. Learn more at cyberark.com.

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At CyberArk, we are moving beyond traditional documentation. We are building a Knowledge Architecture that powers our SaaS transformation and Agentic AI strategy. We are looking for a Senior Technical Content Engineer who views content as structured data. You won't just write topics; you will design the information models that ensure our customers (and our AI agents) can find, trust, and act on information instantly.
Key Responsibilities

• Information Architecture & RAG Readiness: Lead the transition from monolithic docs to granular, metadata-rich content. Ensure all documentation is optimized for Large Language Model (LLM) consumption, focusing on chunking strategy, semantic accuracy, and "RAG-readiness."
• Supportability Engineering: Use support data (Salesforce/Tableau) and product analytics (Mixpanel) to identify friction points. Design "How-to-fix-it" content architectures that preemptively deflect support tickets.
• Guided UX & Microcopy: Partner with Product and UX teams to design interactive, in-product guided workflows. You will treat the UI as the primary documentation surface, reducing the need for external manuals.
• Platform-Wide Governance: Enforce unified standards across product pods. You will be a champion for the Standards & Operations Hub (SOH), ensuring that cross-service workflows are seamless and consistent.
• AI Orchestration: Proactively build and implement AI-assisted workflows (e.g., automated style-checking, content generation pipelines) to increase organizational velocity and quality.

• Systems Thinking: 5+ years in technical documentation with a proven track record of designing content models, not just writing features.
• AI Literacy: Hands-on experience using LLMs to optimize documentation workflows. You understand how AI "reads" content and how to structure data to minimize hallucinations.
• Data-Driven Mindset: Ability to analyze user behavior through analytics tools to prove the ROI of documentation initiatives.
• Technical Proficiency: Expert-level experience with "Docs-as-Code" (GitHub/GitLab, CI/CD) and structured authoring (MadCap Flare or similar DITA-based logic).
• Influence & Leadership: Ability to challenge Product Managers on UX and hold engineering teams accountable for documentation-ready features.