Senior ML​/AI Engineering Manager, GenAI

Overview

Our Company
Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

Our GenAI Experiences Engineering team delivers customer-facing
AI capabilities across Adobe Experience Cloud
. We operate with a startup mentality: rapid delivery of value, iterative learning, and scalable solutions that hold up in production.

As GenAI Experiences mature, we are expanding beyond reactive chat interactions into proactive, grounded, workflow-aware intelligence across Experience Cloud. This role leads the ML/AI squad responsible for building the ML foundations and systems that make that shift possible.

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 ML/AI leadership 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 partner closely with Product, Design, Application Engineering, and Agent/Orchestration counterparts to ensure ML systems are
shippable, measurable, privacy-conscious, and latency-aware, and that they translate into durable product experiences rather than research prototypes.

In this role, you will directly influence Adobe’s ability to deliver differentiated GenAI experiences at scale by building the ML systems that unlock:

• Real-Time Contextual Intelligence - instant page-level insights on the edge
• Predictive User Workflow Engine - learning and predicting intent/next steps/insights over time and accounting for the broader multi-application context
• Natural Language Chat-Based UI Control - turning intent into safe, grounded agents to connect users to cross-application functionality

You will also drive outcomes tied to the roadmap’s experience metrics (examples include engagement with surfaced insights, proactive recommendations, and defining specific benchmarks that align with both ML/AI quality +user experience quality).

At this level, expectation is high leverage: you shape outcomes across multiple roadmaps and teams by establishing
the ML operating model, system ownership, and delivery rigor — not just optimizing within one model or one feature area.

You will lead execution across six persistent ML work streams (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

Key Responsibilities

• Lead the ML/AI squad: hire, mentor, and retain senior ML engineers; build a culture of applied rigor, startup style fast iteration, and measurable…