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The Opportunity

Adobe is reimagining the future of creativity - where generative AI, intelligent agents, and human imagination work hand in hand. As an Engineering Manager, Agentic Product, you will lead a team of engineers building Adobe's Agentic Product: the AI-native experience that brings generative models, creative intelligence, and decades of differentiated Adobe capabilities together into a coherent, high-quality product for creators used by hundreds of millions of people every day. You'll partner with Product and senior engineering leadership to define, build, and ship agentic experiences that meaningfully change how creators work.

You'll be responsible for the day-to-day execution and team health of an engineering squad delivering agent capabilities, behaviors, and experiences across surfaces. This is a hands-on engineering leadership role - you are close to the code, deeply invested in team growth, and accountable for shipping quality software on a predictable cadence.

This is an opportunity to help build a new, AI-native engineering team and practices that will define Adobe's most visible AI product. The right person brings experience leading engineering teams that ship high-quality, user-facing AI experiences, a strong point of view on what "great" looks like for creative AI, and the ability to raise the bar in a space that is moving fast.

What you'll do

• Lead day-to-day engineering execution for a team building Agentic Product capabilities - coordinating delivery, managing dependencies, and maintaining a predictable shipping cadence across surfaces.

• Grow and develop the engineers on your team through coaching, goal-setting, and hands-on technical engagement that builds both individual and team capability.

• Partner with Agentic Product Management to translate product strategy into well-scoped engineering plans, sequence delivery, and surface technical constraints early.

• Contribute to the design and delivery of agent capabilities spanning in-app creative workflows, multi-step task execution, and context-aware assistance across Adobe's surfaces.

• Help establish and maintain the quality bar for agent behavior - what good looks like, how it's measured, and how the team systematically improves it over time.

• Collaborate with platform and infrastructure teams to ensure agent features are built with appropriate evals, guardrails, data protection, and the reliability expected of a product at Adobe's scale.

• Stay current with emerging agentic standards and model capabilities and help your team adopt new tooling and practices without losing execution focus.

What you'll need to succeed

• A track record of leading engineering teams to ship complex, high-quality user-facing AI products with strong execution discipline.

• Solid experience with AI/ML product engineering, including working knowledge of LLM APIs, agent frameworks, and the capabilities and limitations of current generative models in creative contexts.

• Hands-on technical depth: you can engage meaningfully in architecture decisions, review code and designs with a substantive point of view, and recognize good and brittle agent behavior at the implementation level. You remain close to the code and the craft.

• Strong product sensibility - you have intuitions about user experience, you can look at agent behavior and know when it's good or brittle, and you partner with PM and design as a peer.

• Effective cross-functional collaboration with Product, Design, and platform engineering teams, with a bias toward proactive communication and shared ownership.

• Comfort operating in fast-moving, ambiguous environments where the technology, the competitive dynamics, and the user expectations are all rapidly evolving.

• Experience with the quality, reliability, and trust requirements that come with shipping AI features to a large consumer and enterprise audience.

• Demonstrated ability to help teams adopt new ways of working, internalize new tooling, and stay ahead of a rapidly shifting technical landscape without losing execution focus.

• Experience working with LLM providers or contributing to AI product strategy is strongly preferred.