AAI Deployment Program Manager, Cloud Applied AI

Minimum qualifications:

• Bachelor's degree in a technical field or equivalent practical experience.
• 8 years of experience in program management.
• 8 years of experience working with machine learning.

Preferred qualifications:

• 10 years of experience managing complex cross-functional or cross-team projects.
• 10 years of experience working with direct customer executives and stakeholder management.
• Experience with deployment Agentic AI to enterprise customers.

About the job:

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Program Manager at Google, you’ll lead complex, multi-disciplinary projects from start to finish — working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines.

Cloud Applied AI (AAI) powers business growth with Gemini Enterprise. Our portfolio includes Gemini Enterprise for customer experience, along with other vertical and domain packaged solutions. We enable high adoption and speed to value by building solutions that are quickly deployed, delivering new 0-to-1 capabilities with startup agility. Team members operate at the forefront of AI, collaborating directly with model builders with unprecedented speed.

Responsibilities:

• Coordinate cross-functional teams, including solution architects and engineers, to guide GenAI agents from discovery to high-scale production.
• Implement robust testing pipelines and golden datasets to validate LLM prompts, ensuring accuracy, persona alignment, and brand voice.
• Oversee complex enterprise stack connections (CRMs, APIs) while resolving latency, infrastructure, and compliance (GDPR, SOC2) issues.
• Lead executive syncs to transition customers to GenAI architectures, prioritizing high resolution rates and CSAT over static milestones.
• Monitor agent performance metrics to proactively prevent pilot stalls, manage RAG knowledge bases, and relay feature requests to product managers.