Principal Content Strategist, AI Learning
Adobe · San Francisco, CA · Marketing and Strategy
About this role
Adobe is hiring a senior-level Communications Manager in the marketing function based in San Francisco, CA. The posting calls out experience with Express. Compensation is listed at $140,100–$261,150 per year.
- Role
- Communications Manager
- Function
- marketing
- Level
- senior
- Track
- Tech leadership
- Employment
- Full-time
- Location
- San Francisco, CA
- Department
- Marketing and Strategy
- Posted
- May 19, 2026
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Job description
from Adobe careersThe Opportunity
Adobe Experience League is Adobe's global platform for inspiring, educating, and connecting marketers in the age of AI. As Principal Content Strategist for the AI training for marketers initiative, you will lead the full content strategy and execution pipeline. Your scope includes Experience League and beyond. You will define ways to empower marketers to work with AI through micro-learning, use case and workflow-based content. You will also create structured learning experiences that meet learners where they are. This is a cross-platform role requiring you to define and drive a joint content strategy in close partnership with content, product, and marketing partners, leading through influence across organizational boundaries to ensure a cohesive learner experience.
What you'll do
- Define and drive the joint content strategy for the AI for marketers program across Experience League and supporting platforms, partnering closely with the marketing content lead to align on roadmap, formats, and learner outcomes
- Own the curriculum architecture and content roadmap for Experience League, developing micro-learning and AI workflow-based content that drives engagement and measurable skill-building
- Oversee the full content creation process, managing contributors, subject matter experts, and authors while maintaining instructional quality and brand standards
- Author select content directly while enabling and guiding a broader creator network to complete at scale