Manager, AI Learning Enablement & Coaching

Revolution Medicines•Redwood City, CA

11h•$143,000 - $178,000•Hybrid

About The Position

Revolution Medicines is a late-stage clinical oncology company developing novel targeted therapies for patients with RAS-addicted cancers. The company’s R&D pipeline comprises RAS(ON) inhibitors designed to suppress diverse oncogenic variants of RAS proteins. The company’s RAS(ON) inhibitors daraxonrasib (RMC-6236), a RAS(ON) multi-selective inhibitor; elironrasib (RMC-6291), a RAS(ON) G12C-selective inhibitor; zoldonrasib (RMC-9805), a RAS(ON) G12D-selective inhibitor; and RMC-5127, a RAS(ON) G12V-selective inhibitor, are currently in clinical development. As a new member of the Revolution Medicines team, you will join other outstanding professionals in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway. 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.

Requirements

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.
Hands-on experience using AI tools in a professional environment.
Experience coaching or training employees on technology tools, digital workflows, or AI-enabled ways of working.
Strong facilitation skills, including small-group sessions, workshops, office hours, or hands-on learning labs.
Ability to translate AI concepts into clear, practical examples for non-technical audiences.
Successful measurable outcomes in training or organizational development supporting AI capability development.
Experience creating or curating AI learning content, job aids, prompt libraries, or use-case playbooks.
Demonstrated success in a teaching, facilitation, tutoring, or coaching role.
Demonstrated evidence of AI capability through work products including, but not limited to.
ability to select appropriate tools and models depending on work needs, validating AI tool outputs, responsible AI usage.
ability to identify practice opportunities to improve quality, speed, insight, or coordination and collaboration.
uses digital tools in recurring work and improves workflows or deliverables.
shares useful examples, explains what works and does not work, helps others adopt good habits.
Strong understanding of adult learning and applied skill-building approaches.
Strong written, verbal, and organizational skills.
Strong ability to collaborate and influence across all levels and functions.
Ability to work effectively with technical teams, business stakeholders, and learners with varying levels of AI fluency.

Nice To Haves

Experience with ChatGPT Enterprise, Microsoft Copilot, Microsoft 365, Teams, SharePoint, or similar enterprise tools.
Experience in biotech, pharmaceutical, life sciences, healthcare, or another regulated environment.
Familiarity with responsible AI, privacy, information security, and governance expectations.
Experience supporting champion networks, peer learning models, or communities of practice.

Responsibilities

Deliver small-group coaching sessions, office hours, practical learning labs, and role-based working sessions focused on approved AI tools.
Coach employees on applying AI to real work scenarios such as drafting, summarization, research support, analysis, ideation, workflow improvement, and productivity use cases.
Teach employees how to assess where AI adds value, when human judgment is required, and how to validate AI-generated outputs before use.
Reinforce responsible-use expectations for AI in a regulated environment, including privacy, sensitivity, and appropriate use boundaries.
Adapt sessions by role, function, skill level, and confidence level to improve relevance and practical uptake.
Translate real employee needs, coaching themes, and Catalyst Network insights into practical learning experiences.
Gather and refine examples of approved AI use across functions and convert them into reusable demonstrations, exercises, and guided practice.
Help employees connect enterprise use cases to their own workflows and identify immediate next-step applications.
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.
Identify recurring learning gaps and recommend or develop targeted materials to address them.
Partner with the Knowledge Management & Technology Enablement role to ensure content remains organized, current, discoverable, and governed.
Capture feedback from sessions, office hours, surveys, and learner interactions to identify barriers, priority topics, and common questions.
Use feedback to improve coaching formats, content relevance, and training priorities.
Share recurring themes and recommendations with Digital & AI Enablement leadership to inform ongoing program refinement.
Execute AI learning activities in line with the established enablement strategy and roadmap.
Coordinate with subject matter experts and stakeholders to prepare relevant examples, materials, and demonstrations.
Track participation, feedback, session themes, and coaching outcomes.
Support onboarding experiences by contributing approved-tool orientation, practical examples, and foundational AI fluency content for new hires.