Group Product Manager, AI-enabled Business Transformation

• Lead the strategy, design, and execution of the agentic data layer for Cloud's Go-To-Market (GTM) customer data.
• Drive a cross-functional charter spanning Engineering, Data Science, Sales, and Marketing to establish self-healing data loops and real-time account intelligence.
• Architect foundational data systems and processes to enable Gemini Enterprise as an autonomous GTM engine for Cloud users.
• Transform unstructured customer data into structured, actionable intelligence to power AI workloads and streamline business operations.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 years of experience in technical product management.
• 7 years of experience managing data products, including automated data hygiene (e.g., entity resolution, deduplication), building data pipelines optimized for AI workloads (e.g., RAG architectures, LLM grounding), and delivering internal or external data APIs, SDKs, or developer tooling.
• Experience leading cross-functional product initiatives from conception to launch including managing the product goal, go-to-market strategy, and design discussions.
  
• Experience utilizing AI productivity tools to streamline business or development workflows.

Preferred qualifications:

• 10 years of product management experience.
• Experience building data pipelines optimized for AI workloads, such as RAG architectures, LLM grounding, agentic tool-use, and feature stores.
• Experience establishing acceptance criteria and trade-off frameworks (e.g., precision versus recall in entity matching).
• Experience collaborating closely with cross-functional technical teams, including engineers, other PMs, and business stakeholders.
• Experience working on products that rely on complex semantic data, knowledge graphs, or AI evaluation tools.

• Bachelor's degree or equivalent practical experience.
• 10 years of experience in technical product management.
• 7 years of experience managing data products, including automated data hygiene (e.g., entity resolution, deduplication), building data pipelines optimized for AI workloads (e.g., RAG architectures, LLM grounding), and delivering internal or external data APIs, SDKs, or developer tooling.
• Experience leading cross-functional product initiatives from conception to launch including managing the product goal, go-to-market strategy, and design discussions.
  
• Experience utilizing AI productivity tools to streamline business or development workflows.