AI-Ready Knowledge Architect

About the role

We are seeking an AI-Ready Knowledge Architect to play a critical role in designing and maintaining the enterprise information architecture essential for cataloging the organization’s data for self-service understanding and enabling AI-ready data and knowledge usage.

Responsibilities

• Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies to ensure shared understanding, semantic consistency, and discoverability of data and knowledge assets.
• Design and evolve information and semantic models that make enterprise data AI-ready, supporting use cases ranging from traditional analytics and BI to applied machine learning and LLM-based experiences (e.g., search, retrieval-augmented generation, and copilots).
• Operationalize data models, taxonomies, and semantic structures through the Enterprise Data Catalog (Alation).
• Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures to ensure consistency and interoperability across business domains and downstream consumption patterns.
• Confirm and document prioritized metadata elements for key business processes, analytical use cases, and AI-enabled workflows, ensuring alignment with governance standards and risk expectations.
• Identify simplification opportunities—reduce redundancy, converge overlapping datasets, and promote canonical sources to improve trust, efficiency, and reusability across analytics and AI platforms.
• Partner with analytics, data science, and AI engineering teams to ensure information architecture, metadata, and semantic context are sufficient to support explainable, governed, and trustworthy AI outcomes.

Requirements

• 7-10 years of experience working with data, metadata, and reference data frameworks, including experience in metadata management and/or data quality monitoring.
• Experience leading the development of enterprise business glossaries, domain models, and ontologies to enable semantic consistency, shared understanding, and AI ready data usage.
• Understanding of how semantic models, metadata, and knowledge representation enable applied AI and LLM use cases, such as search, question answering, and decision support.
• Strong business acumen in relating data to business process drivers and performance management, with a value delivery mindset.
• Collaborative, team focused delivery experience that drives outcomes across enterprise data, analytics, and technology organizations.
• Excellent knowledge of data and metadata management principles, business analysis, and process engineering.

Skills

• Experience with Knowledge Graphs (e.g., Neo4j, Stardog, Amazon Neptune, Azure Cosmos DB Graph).
• Hands-on experience with graph platforms (e.g., Neo4j, Stardog, Amazon Neptune, Azure Cosmos DB Graph).
• Experience supporting AI/LLM use cases (e.g., search, Q&A, RAG/copilots).
• Experience operationalizing semantic structures through a data/knowledge catalog (e.g., Alation, Collibra, Microsoft Purview, DataHub).

Benefits

• Flexible remote work option.
• Competitive compensation package including a target rate of $85/hr w2.
• Contract length of 07/13/2026 – 12/31/2026.

Pay

• $85/hr w2

Schedule

• Remote work option.