Principal Strategic Program Manager

Adobe•San Jose, CA

3d•$146,300 - $277,400

About The Position

Adobe enables organizations to generate on-brand, commercially safe creative content at scale. As a Principal Strategic Program Manager , you will define and orchestrate AI programs spanning model development, infrastructure, safety, evaluation frameworks, product integration, and enterprise readiness. You will partner directly with senior leaders across ML Engineering, Applied Research, Product, Security, Legal, and Go-to-Market to translate ambitious AI strategy into executable roadmaps with clear and measurable outcomes, and disciplined delivery.

Requirements

Experience with strategic, operational, and technical program management experience delivering complex, cross-functional initiatives
Deep understanding of AI/ML systems, including large language models, model training pipelines, inference systems, evaluation frameworks, and production ML infrastructure
Experience leading large-scale GenAI or AI platform programs in high-growth or startup-like environments
Proven ability to drive alignment among senior technical and product leaders without direct authority
Executive-level communication skills with the ability to distill complexity into clear decisions
Experience operating in enterprise-grade environments with security, compliance, and reliability requirements

Nice To Haves

Thrive in fast-moving environments where priorities evolve quickly
Can move fluidly between strategic architecture discussions and operational execution
Are comfortable challenging assumptions and driving clarity in highly technical debates
Have a bias toward action, ownership , and measurable impact
Care deeply about building responsible, scalable AI systems

Responsibilities

End-to-End AI Program Leadership
Partner with Product to drive the strategy, roadmap, and execution for large-scale GenAI initiatives across research, platform, and product surfaces
Establish program structures, governance models, and success metrics that scale with platform growth
Coordinate interdependent workstreams spanning research, model training, evaluation, inference infrastructure, and product integration
Drive initiatives across model safety, brand controls, governance, data compliance, and enterprise feature capabilities
Align ML engineering, product, design, infrastructure, and business partners on shared goals and execution sequencing
Manage risks, dependencies, and tradeoffs across highly technical teams
Build and maintain program scorecards, dashboards, and executive reporting
Run structured program reviews , scrums, reviews, and operational cadences
Identify adoption blockers, technical debt risks, or scaling constraints early