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Role Summary

The Principal, Knowledge Management & Ontology is accountable for the enterprise semantic layer and knowledge foundations that make generative AI and analytics useful, safe, and scalable. This role owns the structure, semantics, and governance of enterprise knowledge across Snowflake and AI platforms, ensuring consistent business meaning across reporting, analytics, and GenAI use cases.

The role establishes the operating model, ownership model, and lifecycle management processes for AI-consumable knowledge assets. This is production-grade enablement—not experimentation.

Scope & Authority

• Enterprise-wide semantic ownership across Snowflake, analytics, and GenAI platforms.

• Formal decision rights over enterprise ontologies and semantic standards.

• Authority to challenge or block deployments that bypass semantic governance.

• Accountable for production knowledge integrity and lifecycle enforcement.

Enterprise Semantic Layer (Snowflake)

• Own the enterprise semantic layer within Snowflake, including business definitions, metric standardization, and governed data products.

• Align ontologies, knowledge graphs, and Snowflake semantic models to prevent metric drift and conflicting business logic.

• Define standards for semantic modeling across analytics, BI, and AI use cases.

• Establish change management, versioning, and approval workflows for semantic updates.

Ontology & Semantic Architecture

• Design, govern, and evolve enterprise ontologies enabling reasoning, explainability, and disambiguation.

• Establish modeling standards for entities, relationships, attributes, and versioning.

• Ensure interoperability across domains, platforms, and AI systems.

GenAI Enablement

• Embed governed knowledge into RAG systems, knowledge graphs, and agent frameworks.

• Define repeatable onboarding processes for new GenAI use cases.

• Establish guardrails for structured vs unstructured knowledge usage.

• Improve grounding, reduce hallucination, and increase answer consistency through semantic strength.

Knowledge Lifecycle & Governance

• Define and institutionalize lifecycle processes: creation, validation, approval, publication, monitoring, and retirement.

• Establish domain ownership and stewardship models for semantic assets.

• Enforce governance for accuracy, provenance, compliance, and auditability.

• Detect and mitigate semantic drift, outdated content, bias, and leakage.

• Serve as escalation authority for knowledge integrity disputes.

Measurement & Impact

• Improve retrieval precision and recall across GenAI use cases.

• Reduce hallucinations through strengthened semantic foundations.

• Decrease semantic inconsistencies across reporting and AI systems.

• Increase AI trust, adoption, and speed to insight.

Qualifications

• Bachelor’s degree in Computer Science or related field (advanced degree preferred).

• 12–15+ years in knowledge management, data modeling, ontology design, or semantic technologies.

• Demonstrated enterprise-scale ontology or knowledge graph design experience.

• Strong understanding of GenAI architectures, including RAG and agent-based systems.

• Experience in regulated or risk-sensitive environments preferred.

• Executive-level communication skills.

We are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age, race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.