Manager, Learning & Organization Development

Stanford University; Redwood City (CA); Hybrid; USD 125,924 - 149,000; Full time

Job summary

Stanford University is seeking a Manager, Learning & Organization Development to lead the design and delivery of high-impact learning experiences while overseeing learning operations and a delivery team.

The role emphasizes advancing staff AI fluency, building practical AI learning content, and aligning standards across Stanford. You will partner with HR, UIT, LMS teams, and program owners to meet university needs.

Qualifications

• Leadership and people-management experience.
• Experience designing and delivering learning programs.
• Familiarity with AI-enabled learning and responsible-use principles.
• Ability to build partnerships with HR, UIT, LMS teams.

Responsibilities

• Lead and develop a team supporting learning delivery and operations.
• Lead end-to-end design for multiple audiences and develop materials such as guides and toolkits.
• Develop AI learning strategy for staff and translate AI tools into learning experiences.
• Evolve learning environments and test AI-enabled tools with governance.
• Define success measures and synthesize data into insights for program improvements.

Skills

Team leadership

AI aptitude

Stakeholder collaboration

Learning program design

Measurement & evaluation

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

Stanford is at a pivotal moment in how learning and development is evolving, driven by advances in artificial intelligence and changing expectations of how work is performed. In this context, the Manager, Learning & Organization Development sets the standards and operating processes for a comprehensive portfolio of talent and learning programs that balance world-class organizational development with practical AI capability building.

There are two critical components to this role -- both equally important. First, this role leads the design and delivery of high-impact learning experiences, oversees the operational systems that enable quality execution, and manages a team that supports program delivery and improvements. Success requires strong partnership across schools and units to ensure programs meet both university-wide and local needs.

The second is advancing staff AI fluency and practical application through building learning content, experiences, and support tools. The Manager partners across Stanford to align standards, gather early feedback, and create opportunities for staff to experiment and learn in a supportive environment.

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.