Head of AI Delivery
Job Description
This role operates across innovation, execution, governance, and transformation to ensure AI solutions align with Responsible AI principles, regulatory expectations, enterprise architecture, and business priorities.
Summary
The Head of AI Solutions leads enterprise AI solution delivery, translating strategy and product roadmaps into measurable business value. This leader scales trusted, compliant, enterprise-grade AI capabilities from experimentation to production; coordinates delivery across the AI CoE, technology, risk, and business partners; promotes reuse; and accelerates execution against enterprise AI priorities.
Key Responsibilities
AI Innovation and Solution Development
Lead the design, development, and deployment of high-impact AI solutions across business lines
Drive rapid experimentation, prototyping, and pilot execution, converting innovations into enterprise-scale deployments
Oversee priority solution domains, including agentic AI, document intelligence, advanced models, and generative AI applications
Enterprise Value Delivery
Own delivery of measurable outcomes, including revenue growth, cost optimization, efficiency gains, risk reduction, and customer or employee experience improvements
Lead multi-disciplinary teams across ideation, validation, deployment, scaling, and optimization
Partner with technology and product organizations to industrialize AI delivery and establish reusable patterns, platforms, and capabilities
Maintain strong regulatory, risk, ethical, and Responsible AI practices, proactively addressing bias, model risk, privacy, security, and unintended consequences
Provide leadership across the full AI lifecycle including in Ideation and early-stage R&D, Experimentation and validation, Production deployment, Enterprise scaling and optimization
Thought Leadership
Serve as a senior advisor and integrator across decentralized AI initiatives, ensuring alignment to enterprise strategy and investment priorities
Collaborate with business lines, product, technology, risk, legal, compliance, and data teams to embed governance and controls into delivery
Advance research, patents, intellectual property, external partnerships, academic relationships, and industry presence where they strengthen enterprise priorities
Enterprise Adoption & Enablement
Drive enterprise adoption through leadership education, community engagement, “art of the possible” sessions, and use-case discovery
Create, empower, and harmonize multidisciplinary teams across data science, engineering, product, risk, legal, compliance, and business functions
Create a culture of innovation, experimentation, accountability, reuse, and continuous learning
Qualifications
Executive-level leadership experience in AI, advanced analytics, emerging technology, or enterprise-scale digital transformation
Proven track record delivering enterprise technology solutions with measurable business impact
Deep understanding of the AI/ML lifecycle, data ecosystems, model development, and production deployment models
Strong knowledge of Responsible AI, model risk, governance, privacy, security, and regulatory expectations in financial services
Ability to operate across complex, matrixed organizations and influence senior executives, business leaders, risk partners, and technology teams
Advanced degree or equivalent experience in computer science, AI/ML, engineering, analytics, business, or a related field
Preferred Skills and Experiences
Experience leading applied AI teams in financial services or another highly regulated industry
Proven success building and scaling centralized AI delivery functions, such as an AI CoE or equivalent capability
Hands-on AI/ML experience, including familiarity with modern model architectures, generative AI, and agentic AI patterns
Established industry thought leadership, research, patent, academic, or ecosystem partnership experience