Director, Product Management, Cloud AI and Science
Google· enterprise· Internet & Cloud Services· Aug 27, 2026 · 2mo agoPosted 61 days ago
Sunnyvale, CA, USA · New York, NY, USA · San Francisco, CA, USA
In office
Full-time
Director
$210K–$270K est.
15+ years exp
Before you apply
Ghost Signal:
Open 61 days.
Job description
As the Director of Product Management, Cloud AI and Science, you will lead the strategic outlook, product development, and commercialization of Google's enterprise AI agent platforms and domain-specific science models. Sitting at the edge of the AI revolution, your portfolio bridges Google’s enterprise AI and agent infrastructure with groundbreaking research coming out of Google DeepMind (GDM).
In this role, you will have end-to-end ownership of highly strategic product pillars focused on developing advanced, long-running AI agents for scientific discovery, building optimization systems that drive operational efficiency across the enterprise, and scaling the commercial deployment of domain-specific research models onto Google Cloud’s enterprise platforms.
Additionally, you will utilize a unique blend of deep technical comprehension (e.g., scientific computing, agentic workflows, complex evaluation systems), business and commercialization acumen (e.g., enterprise pricing, monetization, and value-packaging strategy), and stakeholder management. You will work with a high-performing team of product managers, collaborate closely with senior engineering leaders, and partner directly with DeepMind research teams to turn raw scientific research into indispensable, high-value enterprise workflows.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $281000 - $391000 (USD) + 30% bonus target + equity + benefits
Learn more about benefits at Google .
• Recruit, mentor, and scale a team of product managers. Define the strategic roadmap to scale our scientific and research model portfolio for enterprise.
• Transition advanced AI agents and model platforms from early access to high-adoption, self-serve production. Establish robust evaluation frameworks and optimize user experiences to meet customer needs.
• Partner with Google DeepMind Research to build highly automated hosting and onboarding systems, accelerating the integration and commercial launch of domain-specific models.
• Structure enterprise billing models and coordinate with Cloud Go-to-Market (GTM) teams to secure external case studies and drive repeatable enterprise adoption.
• Forge highly effective joint roadmaps and operational interfaces with research and core platform engineering teams to rapidly commercialize breakthrough capabilities.
• 15 years of product management experience, delivering technical platform products or enterprise SaaS solutions.
• 5 years of experience hiring, developing, and leading teams of product managers.
• Experience launching products in machine learning, artificial intelligence, large language models (LLMs), or advanced scientific computing.
Minimum qualifications:
• 15 years of product management experience, delivering technical platform products or enterprise SaaS solutions.
• 5 years of experience hiring, developing, and leading teams of product managers.
• Experience launching products in machine learning, artificial intelligence, large language models (LLMs), or advanced scientific computing.
Preferred qualifications:
• Master's degree or PhD in a quantitative scientific field (e.g., Computational Biology, Chemistry, Meteorology, or Computer Science), or an MBA.
• Experience working within or selling to the Healthcare and Life Sciences (HCLS), Quantitative Finance, Public Sector, or Logistics industries.
• Experience pricing and package-structuring 0-to-1 AI and enterprise SaaS products, managing profit and loss (P&L), and driving enterprise software commercial models.
• Understanding of agentic architectures, multi-agent coordination, human-in-the-loop system design, and advanced evaluation methodologies.
• Ability to build relationships and influence senior research scientists (e.g. Google DeepMind) and engineering teams in highly matrixed organizations without direct authority.
Application prep
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