The GBAI team architects and delivers AI-powered, intuitive, and connected solutions to significantly amplify the value GBO brings to customers and partners. GBAI partners closely with Sales teams, gTech's Support, Professional Services, Product Management, and Engineering teams to support advertiser success across the ecosystem. We are leaders of the customer experience, advocating for big-picture goals, feature requests, and offering product improvements backed by data-driven insights. Our work enables business teams to deliver delightful support and services to our customers. The Global Product Senior Lead for Sales AI Infrastructure is a critical, cross-functional role responsible for defining and executing the infrastructure tooling strategy that powers Sales AI initiatives (primarily focused on the Connect AI ecosystem). This role partners with both Sales and Support product teams to build scalable, extensible, and high-velocity tooling solutions that advance our Agentic operations and bridge the gap between Support and Sales. The Go-to-Market Operations (GtM) team ensures Google's complex and ever-evolving Ads business runs smoothly. We are instrumental in setting go-to-market strategy, and ensuring flawless execution and operations against the strategy. We have teams embedded in each of the major Ads business areas as well as global teams that work across the business areas. Team members are analytical and strategic, with a pragmatic sense of how to get things done. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $178000 - $258000 (USD) 20% bonus target equity benefits Learn more about benefits at Google . Responsibilities 3 Partner with gTech, Sales, Product, and Finance, aligning with Director and VP-level stakeholders to synchronize requirements for annual planning. 3 Power the Sales AI quality program, delivering structured evaluation dashboards that leverage autorater outputs to improve model accuracy. 3 Set the strategic tool and platform goal, translating business asks and quantified business cases into prioritized technical roadmaps. 3 Enable the Agentic Development Lifecycle (ADLC), governing agentic skills while analyzing datasets, like AI transcripts, to find growth opportunities. 3 Estimate and measure the operational and business impact of new features, processes, and systemic experiences.