Knowledge Engineer designing and curating enterprise knowledge for AI and operations at Safe-Guard. Collaborating across teams to transform information into structured, reusable knowledge.
Responsibilities
Design and maintain enterprise knowledge structures.
Define information architecture, taxonomy, naming conventions, and metadata standards.
Ensure knowledge is consistent, searchable, and version-controlled across platforms.
Eliminate duplication and drive reuse of authoritative content.
Establish and enforce standard templates for: Policies and procedures, How-to guides and FAQs, Operational playbooks, Decision trees and troubleshooting guides.
Work directly with SMEs, business leaders, and frontline teams to: Elicit tacit knowledge, Convert tribal knowledge into documented standards, Resolve conflicting or outdated information, Facilitate working sessions and reviews to validate content correctness.
Act as a bridge between business teams and AI/IT teams.
Prepare and structure knowledge for seamless reuse in ServiceNow: Incident, problem, and request workflows, Agent assist and self-service portals.
Map enterprise knowledge sources to ServiceNow knowledge models.
Ensure content supports operational resolution, not just documentation.
Partner with AI/ML and platform teams to: Prepare knowledge for GenAI-enabled chat and copilots, Support Retrieval-Augmented Generation (RAG) pipelines, Apply AI-friendly practices: Clear chunking and modularization, Explicit definitions and terminology, Source attribution and traceability.
Help define what content is authoritative vs contextual for AI usage.
Optimize SharePoint and OneDrive content for effective use by Microsoft 365 Copilot.
Ensure permissions, metadata, and content structure align with Copilot access models.
Partner with IT and business teams to identify high-value employee workflows where Copilot can surface trusted knowledge.
Support governance models for Copilot-enabled content usage.
Define ownership, access controls, and approval workflows for enterprise knowledge.
Ensure compliance with data privacy, security, and retention policies.
Maintain auditability and traceability of content used by AI systems.
Support Responsible AI practices by ensuring GenAI consumes approved, accurate sources only.
Educate teams on how to contribute, maintain, and use enterprise knowledge correctly.
Create documentation, guidelines, and best practices for content authors.
Measure adoption, reuse, and effectiveness of knowledge assets.
Continuously improve based on feedback from employees and AI system performance.
Requirements
3–5 years of experience in knowledge management, content engineering, technical documentation, or enterprise enablement roles.
Hands-on experience with Confluence, SharePoint, and OneDrive.
Strong understanding of information architecture, taxonomy, and content lifecycle management.
Experience working cross-functionally with business, IT, and operations teams.
Excellent written communication and content structuring skills.
Ability to translate complex processes into clear, standardized documentation.
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