Principal Product Manager, Research and AI - Data
About The Position
The Research and AI team builds foundational generative AI models and applications for Adobe products, enabling customers to ideate, develop, and scale content in new ways. We're looking for a Principal PM to define and drive our data roadmap, including sourcing and processing training data as we develop the next generation of generative capabilities. This position supports multimodal generative capabilities across images, video, and more. It is a technical role with deep impact, combining data engineering, applied science, and product thinking. You will act as a key connection between the data organization and modeling team to drive real customer impact.
Requirements
- Bachelor’s degree in computer science, engineering, or equivalent experience.
- 7+ years of product management experience, with a significant portion in AI/ML or data-intensive environments.
- Strong technical depth to hold conversations about data pipelines, model training, quality metrics, and evaluation frameworks.
- Ability to translate between technical and non-technical collaborators.
- Detailed thinking to build for scale.
- Proactivity and comfort with ambiguity to refine problem statements and move fast without waiting for perfect information.
- Attitude centered on balancing value, coverage, quality distributions, and downstream impact.
- Great partner collaboration to build trust with engineering, science, legal, and leadership.
Nice To Haves
- Experience with generative AI.
- Experience building tools for creatives and designers.
Responsibilities
- Define and own the data product roadmap, including the end-to-end pipeline to significantly scale training data in generative models.
- Build systems and processes to increase value from data: prioritize what we acquire, how we process it, and ensure it maps directly to downstream model performance needs.
- Translate between modeling requirements and data reality – transform customer asks into concrete, actionable data programs.
- Partner closely with data engineering and applied science to build feedback loops that close the gap between model evaluation and data approach.
- Build institutional knowledge around data decisions - what was included, why, how it was processed - so the team can reason about model behavior and iterate faster.
- Make data health visible to the right collaborators at the right time.
- Partner with legal and collaborators to ensure data programs meet needs around commercial safety.
- Find opportunities to build proprietary data advantages such as reward models.
Benefits
- comprehensive benefits programs
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What This Job Offers
Job Type
Full-time
Career Level
Principal
