AI Strategy Lead

• 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.

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.

• 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.