Principal AI & Knowledge Graph Architect Full Time NYC / NJ area (Hybrid / Telecommute)
Our client is currently seeking a Principal AI & Knowledge Graph Architect to join our Information Technology team. The Principal AI & Knowledge Graph Architect will be responsible for leading the 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 our clients 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 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.
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
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 the 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 in 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.
Familiarity with graph databases, ontology frameworks, and semantic standards.
Experience working with AI vendors, research organizations, or emerging technology ecosystems
Adam Planica Technology Recruiter PRI Technology P: 973.732.5454 x41
C: 917.572.1363 www.pritechnology.com