below marketmost similar roles pay hereabove market
This role pays more than
61%
of similar roles. Most pay
$160,854–$224,306
— the blue band above.
At the midpoint, this role pays about
$198k
versus about
$193k
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
137 open roles
on FindRole.
Listed pay typically runs
$114,000–$253,000
across 82 roles with salary data.
The Enterprise AI Experience & Adoption Lead joins the Enterprise AI team within the Office of the CTO to scale responsible, secure, and high-value AI use across the company. This role involves leading cross-functional programs for AI governance, platform operations, and change management while defining standards for data handling, compliance, and observability. You will partner with technical teams to support well-architected setups using tools like Azure AI Foundry, GitHub Copilot, Langfuse, Neo4j, M365 AI capabilities, and Dash Enterprise. Key responsibilities include driving adoption through training plans, establishing program metrics, and supporting AI FinOps practices like cost optimization and usage tracking. The role solves the business problem of operationalizing enterprise AI platforms while ensuring platform reliability, user experience, and risk management in a global technology environment.
Lead cross-functional programs for enterprise AI platforms, including governance, operations, and lifecycle management.
Define and operationalize standards for responsible AI usage, data handling, compliance, and platform best practices.
Partner with technical teams to support well-architected platform setups for tools like Azure AI Foundry and GitHub Copilot.
Drive AI adoption by creating operating models, training plans, and user engagement feedback loops.
Establish program metrics, governance forums, intake processes, and roadmaps to improve executive decision-making.
Support AI FinOps practices, including usage tracking, cost optimization, and value measurement.
Identify operational risks across AI tools and workflows to drive scalable solutions with stakeholders.
What we're looking for
Bachelor’s degree with 12+ years of experience; or Master’s degree with 8+ years of experience; or PhD with 5+ years of experience; or equivalent experience.
8+ years of experience in technical program management, enterprise technology programs, AI/ML platforms, cloud platforms, data platforms, or digital transformation.
Experience leading cross-functional programs across technical, security, governance, and business stakeholders.
Strong communication and executive presentation skills with the ability to translate technical topics for different audiences.
Experience with enterprise AI, generative AI, responsible AI, AI governance, MLOps, LLMOps, or AI platform operations (preferred).
Familiarity with platforms such as Azure AI Foundry, GitHub Copilot, Langfuse, Neo4j, Microsoft 365 Copilot, Dash Enterprise, or similar enterprise AI tools (preferred).
Experience with governance areas, cloud cost management, platform adoption, developer enablement, or technology change management (preferred).
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