Enterprise AI Platform Governance & Operations Lead
Role details
Job location
Tech stack
Job description
The Enterprise AI team helps Lam scale responsible, secure, and high-value use of AI across the company. The team works across enterprise AI platforms, developer tools, data and knowledge platforms, observability, adoption, and governance to enable teams to build and use AI capabilities with confidence.
The Office of the CTO is where innovation takes center stage. We inspire our global technicalcommunity to take on grand challenges, understand emerging trends, identify the criticalinflections, and drive our sustainability, Environment, Social, and Governance (ESG) practicesthat will define the next generation of semiconductors and continued impact. The impact you'll make
In this role, you will directly contribute to Lam's enterprise AI strategy by helping shape how AI platforms are governed, operated, adopted, and scaled across the company. You will partner across IT, Security, Legal, Data, Engineering, and business teams to enable responsible AI adoption while improving platform reliability, user experience, cost transparency, and operational maturity. What you'll do
- Lead cross-functional programs for enterprise AI platforms, including AI governance, platform operations, adoption, change management, and lifecycle management.
- Help define and operationalize standards for responsible AI usage, access management, data handling, observability, compliance, and platform best practices.
- Partner with technical teams to support well-architected platform setup and operations across tools such as Azure AI Foundry, GitHub Copilot, Langfuse, Neo4j, M365 AI capabilities, Dash Enterprise, and related AI platforms.
- Drive adoption and enablement for AI capabilities by creating clear operating models, communications, training plans, user engagement, and feedback loops.
- Establish program metrics, governance forums, intake processes, roadmaps, and reporting to improve visibility, prioritization, and executive decision-making.
- Support AI FinOps practices, including usage tracking, cost optimization, licensing visibility, and value measurement.
- Identify risks and operational gaps across AI tools and workflows, then partner with stakeholders to drive scalable solutions.
- Work in an onsite-flex model with collaboration across global teams.
Requirements
- 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.
- Experience creating operating models, roadmaps, metrics, executive communications, and change management plans.
- 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.
- Familiarity with platforms such as Azure AI Foundry, GitHub Copilot, Langfuse, Neo4j, Microsoft 365 Copilot, Dash Enterprise, or similar enterprise AI tools.
- Experience with governance areas such as identity and access, data protection, risk management, compliance, auditability, model/application lifecycle, or usage monitoring.
- Experience with cloud cost management, platform adoption, developer enablement, or technology change management.
- Experience working in a large global enterprise or highly regulated technology environment.
- Program or change management certifications such as PMP, Prosci, Agile, Scrum, or equivalent are a plus.
Benefits & conditions
CA San Francisco Bay Area Salary Range for this position: $125,000.00 -$270,000.00.
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.