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A leading investment management firm is hiring a senior AI strategy and enablement leader to define and execute its enterprise-wide AI roadmap. This is a first-of-its-kind leadership role designed for someone who can connect business priorities, technology execution, vendor strategy, and practical AI adoption across the organization.

This person will partner closely with senior technology and operations leadership to identify high-value AI use cases, prioritize initiatives, build internal AI and LLM-enabled solutions, and guide successful rollout across business functions. Over time, this leader will also help build and manage a small AI team.

What You’ll Tackle

• Own enterprise AI product strategy from ideation through delivery and iteration

• Build and prioritize a practical AI roadmap aligned to business value

• Translate ambiguous business needs into clear AI product requirements

• Partner with technology teams on architecture, APIs, infrastructure, model selection, and integrations

• Lead internal LLM and AI solution development in partnership with technical teams

• Evaluate and manage strategic AI vendor relationships

• Drive adoption across investment, operations, finance, distribution, and corporate functions

• Establish scalable AI enablement, governance, and delivery practices

What You Bring

• 10+ years across financial services, technology, product, engineering, or business analysis

• 3+ years focused on AI, ML, LLMs, or enterprise AI implementation

• Experience building, launching, or scaling enterprise AI solutions

• Strong understanding of AI product lifecycle, deployment, integration, and adoption

• Technical fluency across APIs, architecture, model selection, and infrastructure

• Ability to influence senior business and technology stakeholders

• Financial services, asset management, or investment management experience

• Strong communication, prioritization, and transformation leadership skills

• Buy-side investment management workflow experience

• Python, prompt engineering, model training, or data platform exposure

• Databricks, Snowflake, Microsoft Fabric, or similar platforms

• Microservices or Model Context Protocol interface knowledge

• Experience building an AI function or small team from the ground up