AI Strategy Lead

About the job

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

At Google, data drives all of our decision-making. As part of the Finance Data and Analytics (DnA) team, you will use data to inform business, process and product decisions across Google. In this role, you will have the opportunity to transform finance processes using AI. Along with your product team within DnA, you will partner with finance and engineering teams to drive process efficiency and transformation, primarily through agentic and AI solutions.

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Build developer frameworks to accelerate and improve the Business Intelligence (BI) development lifecycle and solutions.
• Help design and build highly reusable, complex skills, agents, and procedures at the AI Platform level that can be leveraged across multiple projects and by both technical developers and non-technical finance stakeholders.
• Act as a strategic zeroth finance customer for Deepmind technology, partnering with core engineering teams on early-stage design, usability, and architecture to ensure new features are optimized for complex, real-world deployment scenarios.
• Act as connective tissue between Finance AI developer, CorpEng, Deepmind and Cloud to define Finance technical requirements, aligning cross-organizational roadmaps, resolving ambiguity, and shipping outcomes that serve both internal and external customers.
• Develop scalable, maintainable internal and external software-as-a-service (SaaS) products decoupled from internal dependencies.

Qualifications

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
• Experience architecting scalable enterprise AI solutions and generative AI pipelines (e.g., Large Language Models (LLMs), LangChain, Vertex AI, or autonomous agents.

Preferred qualifications:

• 9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
• Extensive experience architecting scalable enterprise AI solutions and Generative AI pipelines including Google's AI technology stack.
• Exceptional stakeholder management and communication skills, with a proven ability to navigate ambiguity, influence global leadership, and act as a bridge between core AI researchers, engineers, and non-technical business leaders.