Manager II, Knowledge Governance

Please Note: This is a Utah-based hybrid position which will require some regular in-office days each week. Additionally, employment with BambooHR is contingent on passing both a background and credit check. 

AI at BambooHR
At BambooHR, we’re all about setting people free to do great work, and we believe AI is a powerful partner in that mission. We’re leaning into intelligent tools to streamline our workflows, giving us more time for high-impact innovation. We look for curious, forward-thinking people who are ready to explore how AI can elevate their work and help us reimagine the future of HR.

Essential Job Duties

The Manager II, Knowledge Governance owns the enterprise knowledge architecture and governance strategy that ensures BambooHR’s knowledge is accurate, structured, and optimized for both human understanding and AI performance across the company. This leader defines the long-term vision for AI-ready knowledge systems, establishes governance direction and standards across multiple departments, and drives multi-team programs that improve content quality, findability, and digital resolution at scale. The role guides large-scale initiatives such as enterprise taxonomy and metadata design, platform migrations, content restructuring, and AI knowledge optimization, with formal decision-making authority over governance direction and systems strategy. By partnering with Product, Engineering and AI/ML, Digital Experience, Support Operations, CX Learning & Development, Legal/Compliance, and other business leaders, this role improves retrieval accuracy, reduces duplication, accelerates product readiness, and strengthens the trustworthiness and usability of knowledge across channels.

You will:

Enterprise Knowledge Architecture and Governance Strategy

• Own the enterprise-wide knowledge architecture and governance strategy spanning customer-facing and internal knowledge across multiple departments.
• Define long-term vision and roadmap for knowledge systems that support AI consumption, retrieval performance, and scalable content operations.
• Establish enterprise standards for taxonomy, metadata, tagging, version control, content lifecycle management, and governance operating models.
• Hold decision-making authority over governance direction, tooling/system strategy, and cross-department standards adoption.

AI Knowledge Systems Vision and Optimization

• Partner with Engineering and AI/ML to define and scale AI knowledge requirements (structure, chunking/format guidance, metadata strategies, evaluation signals) that improve grounding and retrieval.
• Drive enterprise improvements in AI knowledge performance, including reduction of hallucinations tied to knowledge issues and measurable gains in retrieval accuracy.
• Establish measurement frameworks for AI knowledge performance and ensure continuous improvement through experimentation and governance controls.

Multi-Department Programs and Strategic Influence

• Own and deliver cross-team programs (e.g., content restructuring, platform updates, knowledge initiatives) that drive operational efficiency and improve customer experience.
• Translate company priorities and division OKRs into cross-functional knowledge programs with measurable outcomes and clear accountability models.
• Proactively manage risk, dependencies, and tradeoffs across departments; ensure sustained adoption of standards and processes.

Content Quality, Risk Management, and Compliance at Scale

• Establish enterprise quality standards that ensure accuracy, completeness, consistency, and compliance across all governed knowledge channels.
• Partner with Legal/Compliance and brand leaders to set scalable review models and controls that reduce risk across customer-facing guidance.
• Lead enterprise remediation efforts when knowledge gaps, inaccuracies, or fragmentation create customer, operational, or AI performance risk.

Function Leadership and Operating Model Ownership

• Lead and evolve the Knowledge Governance function, including org design, hiring plan, and capability development as the enterprise scope expands.
• Set operating rhythms, capacity planning models, intake/governance process