Knowledge Engineering Lead

About the role

The Knowledge Engineering Lead is responsible for designing and maintaining the structural foundation of an AI‑driven customer support knowledge base. This strategic role ensures that information is organized, tagged, and formatted so AI agents can retrieve and apply it reliably.

Key responsibilities

• Own the taxonomy, metadata schema, article formats, and hierarchy of the knowledge base.
• Define and enforce AI‑readiness standards and retrieval quality benchmarks.
• Guide Knowledge Engineers in applying information‑architecture principles to new and existing content.
• Collaborate with AI Support Architects to align knowledge structure with agent behavior and orchestration design.
• Audit the knowledge base continuously to eliminate gaps, redundancy, and poor retrieval performance.
• Lead taxonomy reviews as products, processes, and AI capabilities evolve.
• Partner with Knowledge Operations to maintain content freshness while preserving structural integrity.
• Contribute to tooling decisions for knowledge‑management platforms and AI integration.

Required profile

• 5+ years of experience in knowledge engineering, information architecture, or technical content strategy.
• Proven track record designing taxonomy, metadata, and structured content systems at scale.
• Experience working on AI/NLP or Retrieval‑Augmented Generation (RAG) projects.
• Background in global or enterprise support environments with large knowledge bases.

Required skills

• Taxonomy design and metadata standards.
• Information‑architecture and content modeling.
• Understanding of AI/RAG and how LLMs consume structured knowledge.
• Familiarity with platforms such as Salesforce Knowledge, Zendesk Guide, Confluence or similar.