Head of AI Enablement - Technology, Data and Operations, Wholesale Division

About the role

The Head of AI Enablement, Wholesale Division is a senior technology leader responsible for designing, delivering, and scaling enterprise-grade AI, GenAI, and automation solutions across the Wholesale Division within Truist's Technology, Data and Operations (TD&O) organization.

Responsibilities

• Directs the development and deployment of AI models and data architectures to enhance system accuracy, efficiency, and resilience.
• Champions cross-functional collaboration to integrate AI solutions into business applications and processes.
• Oversees experimentation and performance assessment of AI and data initiatives and makes significant improvements on processes or systems to ensure effectiveness.
• Drives innovation by contributing to intellectual property and advancing AI capabilities within the organization.
• Manages multiple AI and data teams led by mid- to upper-level Management.
• Develops and enforces AI and data governance standards aligned with organizational goals and regulatory requirements.
• Recommends operational plans and strategies with short- to mid-term (0-3 years) impact on job area results.
• Collaborates with stakeholders to identify real-world problems and apply AI and analytics for actionable insights.

Requirements

• Bachelor’s degree in Computer Science, Data Science, AI, Software Engineering, or related field.
• Minimum of 12 years of professional experience in AI and data with progressive management responsibilities.
• Proven experience managing teams and delivering AI and data-driven solutions at scale.
• Strong knowledge of AI models, data architectures, and analytics methodologies.
• Experience with regulatory compliance and risk management in AI and data technologies.

Qualifications

• Bachelor’s degree in computer science, Engineering, Data Science, or related field (advanced degree preferred).
• 10+ years leading product, platform, or applied AI engineering teams in large-scale, high-availability environments.
• Proven experience designing, deploying, and operating production AI, GenAI, and automation systems (LLM-based solutions, agentic architectures, Power Automate/RPA, and ML pipelines) using enterprise, governed tooling (e.g., Copilot, Copilot Studio, Agent Builder, pro-code frameworks).
• Track record of standing up AI intake, prioritization, and governance models across a large, multi-line-of-business organization.
• Demonstrated knowledge of Responsible AI frameworks, model risk governance, and secure data management practices in a regulated financial services environment.
• Ability to build credibility with engineers while influencing Wholesale executives and delivery leaders.