Director, Product Management, Cloud AI and Science

About the role

The Director of Product Management, Cloud AI and Science will lead the strategic outlook, product development, and commercialization of Google's enterprise AI agent platforms and domain-specific science models.

Responsibilities

• 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

Requirements

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.

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.

Skills

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.

Benefits

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

Pay

$281000 - $391000 (USD)

Schedule

N/A

Benefits

N/A