Senior ML/AI Engineering Manager, GenAI Experiences
Adobe · San Jose, CA · Engineering and Product
About this role
Adobe is hiring a senior-level Engineering Manager in the software engineering function based in San Jose, CA. The posting calls out experience with Express, Machine Learning, LLMs and roughly 10+ years of relevant work. Listed education preference: a bachelor's degree or equivalent. Compensation is listed at $178,900–$351,225 per year.
- Role
- Engineering Manager
- Function
- software engineering
- Level
- senior
- Track
- hybrid
- Employment
- Full-time
- Location
- San Jose, CA
- Experience
- 10+ years
- Education
- Bachelor's degree
- Department
- Engineering and Product
- Posted
- Mar 16, 2026
More roles at Adobe
Job description
from Adobe careersThe Opportunity
We are seeking an experienced Senior ML/AI Engineering Manager (M50) to lead the Experience ML/AI squad within GenAI Experiences. This role owns delivery of the ML strategy that moves AI Assistant from a reactive experience (driven primarily by agents) to real-time contextual intelligence, predictive workflow understanding, and safe natural-language UI control across Experience Cloud.
This is a uniquely Experience focused role. We start from user outcomes—how products feel, work, and deliver value—and back into the right mix of ML techniques using UI context and user behavior/workflow signals to build proactive, grounded intelligence across Experience Cloud
This is intentionally scoped for a senior leader who operates beyond a single project or model. Success requires setting strategy and one-year objectives, delegating across direct reports, and making complex tradeoffs where in-depth knowledge of organizational goals and product constraints is required — consistent with M50 expectations.
You will lead execution across six persistent ML workstreams (the organizational unit of delivery), ensuring clear ownership, cross-team dependencies, and reusable ML foundations:
Page & UI Semantic Understanding and Manipulation
User Behavior, Intent & Workflow Analytics
Heterogeneous Object & Graph Modeling
NL Interaction with Cross Product New Services via Agents
Edge Inference & Model Optimization
Human-in-the-Loop Control & Learning