Manager, Learning & Organization Development

Stanford University

Redwood City, Northern (CA, KY)

Hybrid

USD 126,000 - 149,000

Full time

40 hours ago
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Job summary

Stanford University in California is seeking a Learning Program Lead to drive hybrid on-site learning initiatives and AI-enabled improvements. You will lead a team, design learning programs for managers and staff, and collaborate with HR, UIT, and LMS teams to deliver effective experiences.

The role emphasizes building AI fluency, maintaining accessible learning materials, and measuring impact to continuously improve outcomes. Hybrid work with on-site days is expected.

Qualifications

  • Experience leading learning delivery, operations, and improvement.
  • Experience designing learning programs for multiple audiences (managers, staff).
  • Ability to translate AI concepts into accessible learning materials and experiences.

Responsibilities

  • Lead and develop a team supporting learning delivery, learning operations, and continuous improvement.
  • Lead testing with new tools and AI-enabled workflow improvements, document learnings, and scale what works.
  • Build partnerships with key stakeholders to understand learning needs and support program design and delivery.
  • Lead end-to-end program design for multiple audiences (new managers, experienced managers, leaders, and staff).
  • Define meaningful success measures and synthesize data into insights to drive improvements.

Skills

Team leadership
Stakeholder management
Learning program design
AI literacy
Learning platforms management

Job description

Work Schedule: Hybrid work schedule (at least 2 days per week on-site)

Budgeted salary range for this position is $125,924-$149,000 per annum

In this role you will:
1) Lead and develop a team
  • Manage and develop a team supporting learning delivery, learning operations, and continuous improvement.
  • Lead the testing and experimentation with new tools and approaches, including AI-enabled workflow improvements. Research emerging trends, establish clear guardrails, run small pilots, document learnings, and scale what works.
2) Lead the design and delivery of learning programs
  • Build and maintain effective partnerships with key stakeholders (e.g., local HR, UIT, LMS/platform teams, and program owners) to understand learning needs, and support program design and delivery.
  • Lead end-to-end program design for multiple audiences (e.g., new managers, experienced managers, leaders, and staff), including needs assessment, learning outcomes, curriculum design, facilitation plans, and evaluation. Develop and maintain accessible learning materials such as participant guides, facilitator resources, toolkits, and quick-reference aids.
3) Build staff AI fluency and capability (enterprise priority)
  • Develop and continuously refine a practical AI learning strategy for staff that aligns with Stanford’s standards and responsible-use principles.
  • Translate emerging AI tools into accessible learning experiences that build confidence and adoption--covering effective prompting, workflow redesign, quality checks and human review, limitations, and risk mitigation.
  • Advise stakeholders on how AI adoption enhances work, where human judgment is essential, and how to support teams through the transition.
4) Evolve and optimize learning environments and AI-enabled learner support
  • Manage and improve our learning platforms, tools, and methods for engaging learners.
  • Explore and test AI-enabled learning tools (e.g., Q&A assistants, practice prompts, and job aids) that help staff apply learning on the job, with clear guardrails and appropriate governance.
5) Measure impact and continuously improve
  • Define a small set of meaningful success measures for programs and initiatives (e.g., reach, learner confidence, on-the-job application, manager outcomes, and operational KPIs) aligned to clear decisions and actions.
  • Synthesize qualitative and quantitative input (MSF feedback, program outcomes, operational data) into insights and recommendations, collecting data to drive program content and delivery improvements.
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