Principal AI & Graph Knowledge Architect

• Define and own the multi-year strategy and roadmap for Digital Engineering Knowledge Platform.
• Drive the integration of standards intelligence into engineering ecosystems, including CAD/CAE, PLM, MBSE, digital twins, and AI-powered engineering tools.
• Establish a unified digital platform connecting standards, learning, journals, technical content, APIs, and AI-enabled services.
• Explore and operationalize emerging interoperability protocols and frameworks, including MCP, ACP, semantic interoperability standards, and AI orchestration technologies.
• Prioritize enterprise platform capabilities and drive scalable growth across business units, content domains, and external standards ecosystems.

AI, Semantic Intelligence & Engineering Automation

• Define domain-specific AI architecture strategy, including integration of SLMs, LLMs, RAG pipelines, vector databases, and semantic retrieval frameworks.
• Lead architecture for AI-enabled engineering use cases, including:
  • Automated compliance validation
  • CAD/PLM/MBSE integrations
  • AI agent and machine-consumable standards
• Define Human-in-the-Loop (HITL) validation frameworks to ensure trust, technical fidelity, and explainability.
• Establish technical guardrails for AI usage, hallucination mitigation, and authoritative engineering interpretation.
• Partner with vendors and research organizations to evaluate emerging AI and graph technologies.

Governance, Strategy & Enterprise Leadership

• Serve as senior technical authority for digital knowledge architecture and AI-enabled standards transformation.
• Define governance standards for semantic consistency, relationship integrity, validation workflows, and lifecycle management.
• Establish architectural and semantic boundaries for external vendors, partners, and AI providers to protect IP and authoritative meaning.
• Collaborate with SMEs, Standards leadership, Enterprise Architecture, Legal, Product, and Technology teams to align technical transformation with organizational strategy.
• Translate complex AI, semantic, and graph concepts into executive-level guidance, board-ready communication, and strategic recommendations.
• Contribute to future-state digital platform strategy, including monetization, APIs, machine-accessible delivery, and multi-SDO interoperability.

Demonstrated knowledge and expertise across the following areas is required:

• Designing enterprise-scale knowledge graphs, ontologies, semantic models, or AI-enabled information platforms.
• Ability to lead complex technical transformation initiatives involving structured and unstructured data.
• Experience defining governance and validation frameworks in regulated or technically rigorous domains.
• Strong understanding of interoperability standards, APIs, and machine-consumable information architectures.
• Ability to operate as a strategic technical leader across executives, SMEs, technology teams, legal stakeholders, and external partners.
• Exceptional communication and executive presentation skills.

Preferred qualifications include:

• 8+ years of experience in one or more of the following:
  • Knowledge Graphs & Semantic Technologies
• Experience with engineering, manufacturing, industrial, or standards-based domains.
• Exposure to CAD, PLM, MBSE, simulation, or digital twin ecosystems.
• Familiarity with graph databases, ontology frameworks, and semantic standards.
• Experience working with AI vendors, research organizations, or emerging technology ecosystems.