The gTech Strategy and Operations organization ensures gTech’s complex and ever-evolving Ads business runs smoothly. We are instrumental in setting strategy, and ensuring flawless execution and operations against the strategy. Team members are analytical and strategic, with a pragmatic sense of how to get things done.
gSO Ads Product and AI exists to architect and accelerate the Tech-first future of gTech Ads. It does this by integrating Product and AI-led innovation to radically transform customer experience and drive disproportionate growth.As a Strategy and Operations Lead, AI Strategy, you will join the Tech Strategy team and report directly to the Director, gTech Ads Strategy and Operations, Product and AI. The team defines and drives the gTech Tech (Product, AI) strategy and governance playbook, and builds thought leadership in AI applications in gTech Ads.
You will be a key contributor, working with limited guidance, on driving various AI strategic initiatives such as the forward-looking scan for AI impact, the strategic AI narratives, and the gTech Ads' Tech Council, Compute and AI OKRs. This role expects you to turn ambiguous AI opportunities into clear insights and actionable recommendations, and to align resources and direction across teams. You will present results to senior stakeholders and act as the team's subject matter expert on AI in gTech Ads.
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: $152000 - $221000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Drive complex, cross-functional projects with limited guidance to define and execute the gTech Tech (Ads Product, AI) strategy and governance playbook, demonstrating end-to-end ownership of key strategy workstreams.
- Solve complex, ambiguous problems by driving forward-looking scans for opportunities to push AI impact in gTech Ads, translating high-level strategic concepts and scans into concrete, actionable roadmaps and business plans.
- Develop relationships with senior stakeholders to drive gTech Ads AI Agenda, coordinate the gAds Tech Council, drive Compute strategy, and establish rigorous AI OKRs across gSO and GTM teams.
- Influence across teams and align resources to lead strategic AI narratives (annual planning narrative) and establish robust AI and tooling success measures across the portfolios.
- Partner effectively with cross-functional experts to lead cross-Google AI collaboration initiatives (e.g., Mustang, AIT), integrating adjacent workstreams to maximize organizational impact.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 6 years of experience in go-to-market strategy, sales operations, strategy and operations, management consulting, corporate strategy, business operations, or a strategy role at a technology company.
- Experience with AI, generative AI, data processing technologies, performance modeling, or scalable systems.
- Experience working with executive-level clients or stakeholders.
Preferred qualifications:
- MBA or equivalent practical experience.
- Experience in management consulting, corporate strategy, business operations, or an analytical strategy role within a technology company.
- Experience building trusted relationships with senior leadership, leading through influence, challenging status quo, and driving alignment across matrixed organizations.
- Experience applying AI in a business context and using AI tools to frame problems, analyze data, and produce recommendations.
- Ability to navigate ambiguous problem spaces, and to independently structure frameworks and roadmaps to solve them.
- Ability to synthesize complex, ambiguous data sets into clear, compelling, executive-ready narratives, defining and measuring operational metrics and KPIs.