Senior Product Manager (Data Platform)
Explicitly mentions vibe coding and LLM-powered workflows for rapid prototyping and iteration.
About the Role
Senior Product Manager for Adobe's AUP organization, responsible for defining and delivering enterprise-grade data and AI platform capabilities that enable faster insights, operational efficiency, and measurable business outcomes. Own the end-to-end product lifecycle, drive adoption, and work closely with engineering and business stakeholders to advance data platforms, LLMs, and agentic systems.
Job Description
Role
Adobe seeks a Senior Product Manager to lead strategy and delivery for enterprise data and AI platform capabilities within the AUP org. The role focuses on building intelligent, scalable platform capabilities across data, AI, and agentic decision systems to accelerate insights, improve operational efficiency, and drive measurable business impact.
Key Responsibilities
- Define product vision and strategy for enterprise data and AI platform capabilities.
- Own end-to-end product delivery from discovery through launch, including prioritization, execution, and accountability for adoption and impact.
- Develop a deep understanding of the underlying technology stack (distributed data systems, cloud platforms, modern data platforms, LLMs, agentic architectures) to inform product trade-offs and decisions.
- Rapidly prototype and validate ideas using modern approaches (e.g., dbt, Airflow, vibe coding, LLM-powered workflows).
- Drive enterprise adoption and align collaborators across cross-functional teams; influence senior leadership through clear communication and product narratives.
Requirements
- Proven experience building and scaling data- and AI-powered products and platforms.
- Deep expertise in platform product management with solid understanding of data platforms, LLMs, agentic systems, and ML/MLOps workflows.
- Hands-on, builder approach with comfort in rapid prototyping and working knowledge of ML models, Python, system architecture, and agentic frameworks.
- Strong analytical and problem-solving skills; ability to use data to prioritize, measure impact, and optimize outcomes.
- Experience crafting product vision and managing feature intake for complex platforms, balancing long-term strategy with near-term execution.
- Strong collaborator management, influence, and ability to operate in fast-paced, ambiguous environments.
Tech & Tools (called out in description)
- Distributed data systems
- Cloud platforms: Azure
- Modern data platforms: Databricks
- Orchestration/prototyping: dbt, Airflow
- Languages & models: Python, ML models, LLMs
- Patterns: ML/MLOps workflows, agentic architectures/frameworks