Ontology Knowledge Architect

Lam Research

Hybrid

Quick summary

Work type
Hybrid
Location
Fremont, CA
Salary
$166,000–$350,000 / yr
Posted
2 days ago
Closes
Dec 15, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $198k
This role $258k
$128k most similar roles pay here $374k

This role pays more than 88% of similar roles. Most pay $162,000–$235,000 — the shaded band above. At the midpoint, this role pays about $258k versus about $198k for comparable roles.

Based on 240 similar postings.

Employer

About Lam Research

Lam Research Corporation is a leading American supplier of wafer-fabrication equipment and services to the global semiconductor industry.

Lam Research currently has 392 open roles on FindRole.

Listed pay typically runs $105,000–$231,000 across 191 roles with salary data.

Most-posted roles

View all roles at Lam Research

At a glance

TL;DR · Ontology Knowledge Architect

As an AI Ontology Knowledge Architect at Lam Research, you will join the Enterprise AI team to build scalable AI platforms and governed agent architectures that drive innovation and operational excellence. Your role involves defining and implementing enterprise ontology and semantic architecture across various business domains, creating reusable patterns for data pipelines and knowledge graphs, and partnering with domain experts to model processes and decision flows. You will translate architectural concepts into practical implementations, establish standards for ontology-data integration, and ensure AI systems operate within governed boundaries. This hands-on role requires expertise in semantic modeling, graph technologies, cloud ecosystems like Microsoft Fabric and Azure, and a deep understanding of data governance and security principles. Experience with enterprise manufacturing or semiconductor domains is beneficial, as you will work on agentic AI systems that require robust memory, tool use, and human oversight mechanisms.

What you'll do

  • Define and evolve Lam’s enterprise ontology and semantic architecture.
  • Design and implement reusable patterns connecting various AI systems and data pipelines.
  • Model enterprise domains with domain experts for use by agents and applications.
  • Translate architectural patterns into working implementations that delivery teams can adopt.
  • Create standards for ontology-data integration, including schema mapping and metadata enrichment.
  • Establish architecture for AI-ready knowledge assets, including semantic analysis and embeddings.
  • Design secure and governed connections for MCP servers and agent actions in ontology-aware workflows.

What we're looking for

  • 12+ years of experience in enterprise architecture or related technical leadership roles.
  • Hands-on experience designing and implementing large-scale data and knowledge graph architectures.
  • Strong understanding of data pipelines, metadata governance, and security principles.
  • Experience with modern cloud AI ecosystems and ontology platforms like Microsoft Fabric, Azure.
  • Ability to translate architectural patterns into working implementations for delivery teams.

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