We are looking for a Knowledge & AI Enablement Manager with proven experience in Knowledge Management and AI driven systems to design, build, and own the complete Knowledge Lifecycle for Technical Support.
This role defines how operational knowledge is created, governed, maintained, and embedded into daily Support workflows, while ensuring it is AI ready and serves as a trusted, high quality input for AI models across the organization.
Key Responsibilities:
Knowledge Lifecycle Ownership:
Own and build the end-to-end Knowledge Lifecycle for Support, from case-driven knowledge creation through continuous improvement and reuse
Define how knowledge is captured from cases, incidents, and escalations and transformed into structured, reusable, high-impact assets
Establish governance models for knowledge quality, validation, ownership, versioning, and ongoing maintenance
Design and operationalize workflows that embed knowledge creation, review, and updates into daily Support activitie
Define and implement a RACI model for knowledge creation, review, approval, and maintenance
Knowledge and AI Readiness:
Own KM platform configuration, Search and analytics tooling, taxonomy, publishing workflows, and integration with case management and AI retrieval pipelines
Define and enforce standards that ensure Support knowledge is structured, tagged, and maintained to be fully consumable by AI systems such as LLMs, RAG pipelines, semantic search, automation, and recommendation engines
Partner closely with Data, AI, and Engineering teams to align knowledge models, structure, and lifecycle with AI consumption requirements and future AI roadmaps
Act as the primary owner of the Support knowledge layer that feeds AI, ensuring consistency, reliability, and scalability
Measurement, Feedback, and Adoption
Define, track, and continuously improve KPIs including knowledge coverage, freshness, reuse, case deflection, and measurable AI performance impact
Establish feedback loops that surface insights from AI usage and knowledge gaps back to Support Engineers, driving better case handling and higher quality knowledge creation
Lead change management initiatives to drive adoption, accountability, and consistent knowledge behaviors across global Support teams.
Requirements: Minimum 5 years of experience in Knowledge Management within B2B systems or organizations (Salesforce Knowledge, SearchUnify, Confluence, etc.)
Bachelors degree in a relevant field (e.g., Information Systems, Knowledge Management, Business Administration, or similar) - required.
Hands-on experience working with AI systems that consume enterprise knowledge, including LLM-based solutions, RAG, or semantic search
Strong understanding of how knowledge structure, quality, and governance directly impact AI accuracy and effectiveness
Experience designing scalable, governed information and knowledge processes
Proven ability to translate strategy into operational execution
Strong stakeholder management and cross functional leadership skills
Fluent English, spoken and written
Nice to Have
Experience in Support Operations or Technical Support environments
Familiarity with case management platforms and self-service deflection models
Experience with taxonomy design, information architecture, and content lifecycle management.
This position is open to all candidates.