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Google

Senior AI Product Operations Manager, Growth AI Transformation

Google New York, New York, United States · $176K–$256K/yr

Software Development · 10,001+ employees

7 h ago
Principal (10+ yrs) Full-time United States
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About the role

The role involves scoping and delivering agentic marketing workflows to drive growth and innovation across Google Marketing. You will define long-term user experience strategies and partner with cross-functional teams to translate functional knowledge into structured formats for AI agents.

What they look for

Generative AI LLM Orchestration Product Management Management Consulting Data Analysis UX Strategy Information Architecture MarTech Architecture RAG Systems Semantic Search Cross-functional Leadership Growth Strategy Agentic Workflows Technical Strategy Performance Optimization

Requirements

Candidates must have at least 11 years of experience in management consulting, product management, or analytics within a technology company. Proficiency in Generative AI, LLM orchestration, and UX strategy is required, along with a bachelor's degree.

Benefits

Bonus Equity Health Insurance

Full description

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 11 years of experience in management consulting, product management and strategy, or analytics in a technology company.
  • Experience working with and analyzing data, and managing multiple cross-functional programs or projects.
  • Experience working Generative AI Agent Capabilities & LLM/Model Orchestration.
  • Experience with User Experience (UX) Strategy & Information Architecture.

Preferred qualifications:

  • Experience integrating LLMs or agentic tools into production-ready web environments or growth-focused workflows (e.g., autonomous journey orchestration, algorithmic brief generation).
  • Ability to analyze situations at a system level, understanding how technical and organizational components interrelate over time within agentic ecosystems.
  • Ability to build and test code quickly to solve targeted problems while maintaining clean, reusable structures for future patterns.
  • Skilled in utilizing analytics to diagnose root causes of agent failure and optimize performance.
  • Expertise in designing MarTech architectures or AI-driven growth applications.

About the job:

The Growth AI Transformation team is the central marketing team driving Owned and Operated (O&O) growth agentic innovation for all of Google Marketing. Our mission is to collapse the latency between strategy and execution shifting away from vanity metrics like volume of output toward true agentic impact, velocity, and value realization.

As an AI Marketing Solutions Architect on the Growth AI Transformation team, you will be responsible for the end-to-end product scoping and delivery of key O&O agentic workflows, moving beyond traditional campaign management to engineer the future of autonomous growth. In this role, you will advocate long-term product strategy across multiple teams, ensuring our intelligent systems are not just dreaming, but plotting a viable course for global scale.

Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems--from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can--changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $176000 - $256000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

  • Design and structure "prompt-aware" content to ensure AI agents provide accurate, empathetic responses, determining when deterministic context vs. LLM reasoning is required.
  • Organize, tag with metadata, and chunk internal data to optimize Retrieval-Augmented Generation (RAG) and semantic search systems.
  • Analyze failed agent runs and awkward handoffs to identify context gaps, implementing real-time fixes to the agent knowledge base.
  • Partner across Product, Legal, and Brand teams to harvest and translate functional knowledge into structured formats digestible by AI agents.
  • Define durable, long-term user experience strategies across multiple teams, drive cross-functional alignment on complex/open-ended challenges, and mitigate unintentional harm in agentic ecosystems.