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Job Details
Posted date: May 08, 2026
Location: Seattle, WA
Level: Director
Estimated salary: $235,000
Range: $192,000 - $278,000
Description
Define and lead a product idea, strategy, and roadmap for key AI Operations areas, always prioritizing measurable improvements for customers. Advocate for customers, drive user research, market analysis, and data analysis to understand workflows, pain points, and unmet needs. Drive product launches with a focus on customer adoption and success. Develop go-to-market strategies, training materials, and communication plans that clearly articulate the value proposition. Engage with stakeholders across different product areas to ensure AI Ops solutions seamlessly integrate and amplify efforts to improve reliability and efficiency. Stay at the forefront of the AI/ML landscape to identify novel approaches and technologies that can be applied to anticipate and solve the next generation of operational challenges for customers.In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. The team works closely with creative developers, designers, marketers, and more to help design and develop technologies that improve access to the world's information. The team is responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring solutions to users.
As a Senior Product Manager for AI Operations, you will partake in driving the strategy and execution of artificial intelligence solutions to transform production operations. Your work will impact engineers, empowering them with AI to predict, prevent, diagnose, and resolve issues with speed and effectiveness.
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.
The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Qualifications
Minimum qualifications: Bachelor's degree or equivalent practical experience.8 years of experience in product management or related technical role.
3 years of experience taking technical products from conception to launch (e.g., ideation to execution, 0 to 1, etc.). 3 years of experience developing/launching products/technologies within one or more of the following: Cloud, SaaS, enterprise, internal tools, or supply chain networks.
Preferred qualifications: MBA degree or equivalent technical degree or a technical background/aptitude. Experience defining and launching successful technical products leveraging AI/ML. Experience with distributed systems, cloud infrastructure, and production operations. Experience with data analysis, machine learning concepts, and AI development lifecycles. Knowledge of production operations and Site Reliability Engineering (SRE) principles and practices.
Extended Qualifications
Bachelor's degree or equivalent practical experience.8 years of experience in product management or related technical role.
3 years of experience taking technical products from conception to launch (e.g., ideation to execution, 0 to 1, etc.). 3 years of experience developing/launching products/technologies within one or more of the following: Cloud, SaaS, enterprise, internal tools, or supply chain networks.