Senior Product Manager, AI Data Intelligence

About the role

Transform Google from a company that uses AI to a company that is powered by AI. As a Senior Product Manager within Google’s Core AI-Powered Data (AIPG) program, you will drive product leadership to transform critical data journeys within the Antigravity ecosystem.

Responsibilities

• Define and deliver a goal and strategy for this space.
• Lead the discovery and development of new tools, skills, and sub-agents that address the evolving needs of teams navigating critical data journeys.
• Build out and operationalize the necessary evaluation frameworks (evals) and analytics to ensure each journey improves the velocity and precision of Google's data insights.
• Conduct research and analysis to identify emerging trends and opportunities in the agentic data space.
• Drive cross-functional collaboration across teams to ensure successful product launches, adoption, and integration by communicating effectively with stakeholders at all levels, including engineers, analysts, executives, and internal product partners.

Requirements

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in product management or related technical role.
• 5 years of experience as a Product Manager specifically managing data products, data platforms, or AI features.
• Experience in defining metrics, building evaluation frameworks, and interpreting data telemetry (e.g., user interaction loops, multi-turn conversational trajectories, or system logs).
• Experience in working directly with databases, data architectures, or business intelligence systems.

Preferred qualifications

• Master's degree in a technology or business related field.
• Experience building and scaling platform features or workflow automation tools that drive internal operational transformation at an enterprise scale.
• Experience in Data Science or Advanced Data Analysis using large-scale data platforms to train, test, and iterate on AI/LLM models.
• Experience building/optimizing AI agents, agentic workflows, or autonomous sub-agents utilizing advanced LLMs or AI-developer tools (e.g., Claude Code or equivalent code-generation agents).
• Strong background in Agent Observability and Performance Analytics evaluating how AI agents are performing, diagnosing failure points in agent trajectories, and measuring their business impact.

Skills

Not specified

Benefits

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