Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 years of experience in product management or related technical role.
• 5 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc).
• 3 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, Typescript or comparable languages.

Preferred qualifications:

• Master's degree in a technology or business related field.
• Experience in a forward-deployed model, working with operational teams or customers to architect technical solutions.
• Demonstrated coding proficiency (e.g., Python, JavaScript/TypeScript) with the ability to build and debug working applications, understand APIs/Webhooks, and navigate a codebase.
• Proficiency with modern AI coding assistants and agentic orchestration tools to accelerate development velocity and build production-ready logic from scratch.
• Track record of operating with a founder mindset, prioritizing high-velocity shipping, rapid learning, and creative problem-solving over rigid processes.
• Deep familiarity with the LLM landscape, agentic architectures, and complex workflow orchestration.

About the job

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.

The AI2 Innovation Accelerator aims to solve Google's Innovator's Dilemma in the AI era. We act as a high-velocity "de-risking engine" for disruptive, high-reward ideas that typically struggle to get prioritized within OKRs and established product roadmaps. We utilize a Venture Studio model, investing in entrepreneurial founders, removing coordination headwind and bureaucratic bottlenecks to enable them to execute quickly, fail-fast, and learn and iterate. We are embedded within AI2 as an organization, which partners deeply with Product Areas (PAs) across Google to identify their highest priority business objectives. We aim to transform Google's industry-leading research into tangible revenue and adoption at unprecedented speeds.

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: $240000 - $334000 (USD) 25% bonus target equity benefits

Learn more about benefits at Google .

Responsibilities

• Deploy directly into partner organizations for focused, immersive engagements to co-build bespoke, high-impact AI solutions from the ground up.
• Drive fundamental workflow redesign from within partner teams, shifting legacy manual processes to autonomous systems where humans act as strategic approvers rather than manual executors.
• Architect and implement agentic workflows across complex enterprise environments, targeting critical use cases like accelerating data center construction diligence, optimizing supply chain inventory buffers, or automating predictive infrastructure maintenance.
• Utilize AI-native development tools to rapidly build full-stack applications and live demos, validating desirability and technical feasibility before heavy engineering investment.
• Engineer continuous evaluation loops with structured human-in-the-loop checkpoints, ensuring agents capture valuable thought traces, learn from real-world edge cases, and autonomously improve over time.