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Open nowFirst seen 9 hours ago

Senior Product Manager, Agentic Systems

Google3,111 open roles

Where
Mountain View, CA, USA
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Your applicationOpen nowSenior Product Manager, Agentic SystemsGoogle · Mountain View, CA, USA
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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 27 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.2%30 days
This job: first seen 9 hours ago

Google median: 27 days open

The posting

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in product management or related technical roles, shipping technical, platform, data, or AI-powered products.
  • Experience in Generative AI, LLMs, and agent-based systems.
  • Experience managing stakeholders.

Preferred qualifications:

  • Experience with digital advertising platforms, campaign optimization, or automated workflow systems.
  • Experience defining quality metrics for new, AI-driven user experiences.
  • Experience designing collaborative UX or multi-agent systems, or with advanced system evaluation and optimization.
  • Experience communicating and collaborating cross-functionally.

About the job

At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.

In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.

One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.

Our team builds generative AI products that empower Google's Global Business Organization to scale Google Ads business growth worldwide. We develop autonomous systems that synthesize vast amounts of advertising data and market signals into actionable insights and engaging narratives. Our flagship product, the Growth Advisor Agent (GAA), enables thousands of sellers to identify and capture significant growth opportunities for advertisers by transforming complex data into clear, data-driven stories.

Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.

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

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Drive GAA from pilot rollout through full General Availability, scaling robust multi-agent workflows to thousands of enterprise users worldwide.
  • Architect the 2027+ direction to evolve GAA into an "always-on growth architect"—pioneering multi-agent orchestration, interactive co-creation canvases, granular UX steerability, and proactive AI triggers.
  • Orchestrate complex integrations across partner AI teams for unified intent routing, deep insight reasoning, and automated deck rendering.
  • Lead continuous evaluations and quality hill climbing by overssing state-of-the-art evaluation pipelines—combining Large Language Model (LLM) autoraters, human-in-the-loop reviews, and inline citations—to ensure robust factuality, grounding, tone, and low latency.
  • Design continuous feedback loops and contextual memory systems that leverage real-world usage to fuel a compounding growth flywheel, sharpening pitch narrative relevance, personalization, and conversion rates.
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