Director, Product Management, Firefly Custom Models

Adobe Adobe · Enterprise · San Jose, CA

Director of Product Management for Adobe's Firefly Enterprise team, focusing on defining and driving the strategy for training generative AI models using enterprise brand assets. This role involves end-to-end ownership of the custom models experience, including user-facing features, integration into Adobe applications, and extending to new modalities. It requires leadership of a PM team, deep expertise in generative AI and MLOps, and close collaboration with research, engineering, and enterprise customers.

What you'd actually do

  1. Define vision, strategy, and roadmap for custom and 3P models.
  2. Lead and mentor a high-performing PM team.
  3. Drive end-to-end product lifecycle: ideation to optimization.
  4. Partner with research, engineering, data/ML, design, and business teams to deliver scalable, reliable solutions.
  5. Stay ahead of AI trends, regulations, and security.

Skills

Required

  • 10+ years in product management
  • 3–5 years in AI/ML leadership
  • Proven success building and scaling custom models
  • Proven track record of successful partnership with research teams
  • Strong technical fluency in ML/AI systems including MLOps
  • Expertise in metrics, analytics, and data-driven decision-making
  • Exceptional communication and ability to influence at all levels
  • Agile and AI first product development experience
  • Experience working with Enterprise SaaS
  • Customer facing rigor and experience with matrixed orgs

Nice to have

  • Hands-on with LLMs, agent frameworks, orchestration, and advanced AI
  • Experience delivering automation at scale with measurable impact
  • Familiarity with responsible AI, security, and compliance
  • Advanced degree (MS, MBA) or equivalent experience

What the JD emphasized

  • custom models
  • brand assets
  • generative AI models
  • enterprise creative
  • custom and 3P models
  • Model lifecycle
  • training/inference efficiency
  • building and scaling custom models
  • ML/AI systems including MLOps

Other signals

  • Define vision, strategy, and roadmap for custom and 3P models.
  • Drive end-to-end product lifecycle: ideation to optimization.
  • Model lifecycle with workflows for ingestion, rights, evaluation, deployment, versioning, monitoring, and deprecation.
  • MLOps, partnering on training/inference efficiency, latency, and throughput.
  • Proven success building and scaling custom models.
  • Strong technical fluency in ML/AI systems including MLOps.