Principal AI & Knowledge Graph Architect

Principal AI & Knowledge Graph Architect

ASME is seeking a Principal AI & Knowledge Graph Architect to join our Information Technology team. The Principal AI & Knowledge Graph Architect will be responsible for leading ASME's technical transformation of engineering standards into intelligent, machine-interpretable digital assets. This role combines expertise across AI systems architecture, knowledge engineering, ontology design, graph technologies, and enterprise-scale digital transformation. It requires balancing innovation with governance ensuring ASME's retention of authority, traceability, and control over the digital meaning of its intellectual property.

Key responsibilities include:

Knowledge Graph & Digital Asset Architecture

• Define and own the multi-year strategy and roadmap for ASME's Digital Engineering Knowledge Platform.
• Drive the integration of ASME 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 ASME's 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
• AI-assisted engineering workflows
• Intelligent standards retrieval
• 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 ASME's 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 ASME 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:
• Enterprise Architecture
• AI/ML Systems Architecture
• Knowledge Graphs & Semantic Technologies
• Data & Information Architecture
• Digital Platform Engineering
• Experience with engineering, manufacturing, industrial, or standards-based domains.
• Exposure to CAD, PLM, MBSE, simulation, or digital twin ecosystems.
• Fami…