Manager, AI Learning Enablement & Coaching

Job description

Revolution Medicines is a global, commercial-state oncology company dedicated to discovering, developing and delivering innovative medicines for patients with RAS-addicted cancers. Leveraging its differentiated RAS(ON) tri-complex inhibitor platform, the company is advancing a broad, integrated portfolio of oral RAS(ON) inhibitors designed to directly target the active, cancer-driving state of RAS. Founded on rigorous scientific inquiry and a willingness to challenge long-held assumptions, Revolution Medicines is committed to changing the trajectory of disease for patients with RAS-addicted cancers worldwide.

Our people are united by a shared way of working: follow the science, challenge assumptions, act with urgency and hold ourselves to a high standard of rigor—all in service of patients.

The Opportunity:

We are seeking a Manager, AI Learning Enablement & Coaching to drive practical adoption of approved AI tools across the enterprise through hands-on coaching, small-group and use-case-based learning. This role will translate established AI enablement strategy into applied learning experiences that help employees use AI tools effectively, responsibly, and confidently in day-to-day work.

This is an execution-focused role centered on behavior change and applied capability building. The role will help employees understand where AI can create value, how to validate outputs, how to use approved tools appropriately in a regulated environment, and how to apply AI to real work scenarios across functions.

Key Responsibilities

AI Coaching and Applied Enablement

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Deliver small-group coaching sessions, office hours, practical learning labs, and role-based working sessions focused on approved AI tools.

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Coach employees on applying AI to real work scenarios such as drafting, summarization, research support, analysis, ideation, workflow improvement, and productivity use cases.

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Teach employees how to assess where AI adds value, when human judgment is required, and how to validate AI-generated outputs before use.

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Reinforce responsible-use expectations for AI in a regulated environment, including privacy, sensitivity, and appropriate use boundaries.

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Adapt sessions by role, function, skill level, and confidence level to improve relevance and practical uptake.

Use-Case-Based Learning

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Translate real employee needs, coaching themes, and Catalyst Network insights into practical learning experiences.

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Gather and refine examples of approved AI use across functions and convert them into reusable demonstrations, exercises, and guided practice.

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Help employees connect enterprise use cases to their own workflows and identify immediate next-step applications.

Learning Content and Resource Curation

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Curate practical learning resources such as prompt examples, job aids, quick-reference guides, FAQs, recordings, and self-paced materials based on employee demand, define and track effectiveness measures.

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Identify recurring learning gaps and recommend or develop targeted materials to address them.

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Partner with the Knowledge Management & Technology Enablement role to ensure content remains organized, current, discoverable, and governed.

Feedback and Continuous Improvement

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Capture feedback from sessions, office hours, surveys, and learner interactions to identify barriers, priority topics, and common questions.

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Use feedback to improve coaching formats, content relevance, and training priorities.

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Share recurring themes and recommendations with Digital & AI Enablement leadership to inform ongoing program refinement.

Program Execution

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Execute AI learning activities in line with the established enablement strategy and roadmap.

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Coordinate with subject matter experts and stakeholders to prepare relevant examples, materials, and demonstrations.

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Track participation, feedback, session themes, and coaching outcomes.

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Support onboarding experiences by contributing approved-tool orientation, practical examples, and foundational AI fluency content for new hires.

Required Skills, Experience and Education:

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8+ years of experience in training delivery, coaching, learning enablement, digital adoption, technology enablement, or a related field including teaching or tutoring in technical fields.

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Hands-on experience using AI tools in a professional environment.

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Experience coaching or training employees on technology tools, digital workflows, or AI-enabled ways of working.

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Strong facilitation skills, including small-group sessions, workshops, office hours, or hands-on learning labs.

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Ability to translate AI concepts into clear, practical examples for non-technical audiences.

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Successful measurable outcomes in training or organizational development supporting AI capability development.

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Experience creating or curating AI learning content, job aids, prompt libraries, or use-case playbooks.

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Demonstrated success in a teaching, facili

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