AI Transformation Lead

Total Experience : 15 – 20 Years

Required 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 Qualification

Experience leading applied AI teams in financial services or other highly regulated industries
Success building and scaling centralized AI delivery functions such as an AI Center of Excellence
Hands‑on AI/ML experience with modern model architectures, generative AI, and agentic AI patterns
Established industry thought leadership, research, patents, academic, or ecosystem partnership experience
Experience managing large, cross‑functional teams across business, technology, and risk disciplines

Key Responsibilities

AI Strategy & Transformation

• 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

Business alignment & Delivery Excellence

• 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

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
• Move ideas from experimentation and prototyping into production-ready, commercially viable, enterprise-scale capabilities
• Oversee priority solution domains, including agentic AI, document intelligence, advanced models, and generative AI applications
  
  
  

Enterprise platforms & AI Governance

• Drive enterprise adoption through leadership education, community engagement, “art of the possible” sessions, and use-case discovery
• Build, 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