Ontology Knowledge Architect

About the role

The group you’ll be a part of, Enterprise AI, is building the foundation for Lam’s AI-first future. We partner across business, data, engineering, security, and technology teams to create scalable AI platforms, governed agent architectures, AI-ready knowledge assets, and reusable solution patterns that help Lam accelerate innovation, improve operations, and turn proprietary domain expertise into durable enterprise advantage.

Responsibilities

• Define and evolve Lam’s enterprise ontology and semantic architecture across business objects, relationships, decisions, actions, permissions, events, and AI-ready knowledge assets.
• Hands-on design and implementation of reusable patterns that connect source systems, data pipelines, metadata, semantic models, knowledge graphs, AI Search, vector stores, MCP tools, and agent orchestration frameworks.
• Partner with business domain experts to model enterprise domains, processes, decision flows, operational states, and domain-specific knowledge for use by agents, copilots, applications, analytics, and automation.
• Create standards for ontology-data integration, including schema mapping, master-data alignment, graph design, metadata enrichment, lineage, observability, versioning, and access control.
• Establish architecture for AI-ready knowledge assets, including structured and unstructured knowledge, semantic analysis, knowledge extraction, embeddings, retrieval, and feedback loops.
• Design how MCP servers, APIs, tools, data services, and agent actions should be represented, secured, governed, and connected into ontology-aware AI workflows.
• Collaborate with AI solution architects, data architects, platform engineers, security, IAM, governance, and domain teams to ensure agents operate with grounded context, trusted actions, and appropriate human oversight.
• Evaluate emerging ontology and knowledge platform capabilities and recommend patterns that balance speed, interoperability, portability, cost, governance, and long-term enterprise differentiation.
• Build reference architectures, standards, decision frameworks, implementation patterns, and governance models for ontology and knowledge lifecycle management.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related technical field; Master’s or PhD preferred.
• 12+ years of experience in enterprise architecture, data architecture, knowledge architecture, semantic modeling, AI architecture, or related technical leadership roles.
• Hands-on experience designing and implementing enterprise-scale data, semantic, ontology, or knowledge graph architectures across complex business domains.
• Strong understanding of data pipelines, data integration, metadata, lineage, governance, access control, data quality, and data product design.
• Experience with ontologies, taxonomies, semantic models, graph models, knowledge graphs, business object models, or domain-driven design.
• Familiarity with modern cloud data and AI ecosystems such as Microsoft Fabric, Azure, Databricks, Synapse, AI Foundry, graph databases, vector stores, search platforms, or comparable technologies.
• Experience building AI-ready knowledge patterns for LLMs, copilots, retrieval-augmented generation, agent orchestration, semantic search, or decision-support applications.
• Understanding of MCP, API-based tool integration, agent-tool interaction patterns, and security/governance considerations for AI systems that access enterprise tools and data.
• Ability to move fluidly between strategy and execution—creating architecture direction while also working directly with teams to implement, validate, and refine it.
• Strong communication skills, including the ability to influence senior leaders and create clear architecture artifacts, standards, and roadmaps.

Preferred Qualifications

• Experience with ontology or operational AI platforms such as Palantir Foundry / AIP, Microsoft Fabric / Fabric IQ, or comparable enterprise semantic and AI platforms.
• Familiarity with enterprise manufacturing, semiconductor, supply chain, engineering, product lifecycle, quality, finance, or operations domains.
• Experience designing and delivering architectures for agentic AI systems, including grounded context, memory, tool use, action governance, feedback loops, and human-in-the-loop controls.
• Strong understanding of security, IAM, least privilege, auditability, and responsible AI principles for enterprise AI systems.
• Ability to balance near-term delivery with long-term architecture direction in a rapidly evolving AI landscape.

Who We’re Looking For

We are looking for someone who can define and evolve Lam’s enterprise ontology and semantic architecture, and who can translate architecture into working implementations, prototypes, platform patterns, graph structures, semantic services, and integration designs that delivery teams can adopt and scale.

Salary

CA San Francisco Bay Area Salary Range for this position: $144,000.00 - $316,000.00. The above salary range for this position is relevant to applicants that reside or work onsite in the California, San Francisco Bay Area only. Salary offers will depend on factors that include the location you work from, your level, education, training, specific skills, years of experience and comparison to other employees already in this role. Actual salary may vary from salary offered due to numerous factors including but not limited to unpaid time off, unpaid leave, company mandated shutdown, and other relevant factors.