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. Reporting directly to the Chief Wholesale Divisional Technology, Data and Operations Officer, this leader partners with business executives, product managers, and engineering teams to translate business requirements into scalable, production-ready AI applications that drive measurable value across Payments, Treasury & Wholesale Digital, Wholesale Lending & Sales Enablement, Investment Banking & Capital Markets, Wealth, and Production Support. This role is hands-on and technically deep, blending engineering fluency in LLMs, agentic frameworks, and applied ML with the ability to engage directly with business stakeholders. Acting as both architect and catalyst, the Head of AI Enablement owns the division's AI operating model, moving demand from a large, un-sequenced inventory into prioritized, routed, and governed delivery. This includes owning a portfolio of use cases and a value pipeline, with a clear mandate to turn inventory into decisions and measure realized benefits, not just track delivery. Acting as both architect and catalyst, the Head of AI Enablement leads cross-functional teams to design and operationalize AI solutions including: • Real-time teammate assist and knowledge retrieval • Conversational AI (voice and chat) • Intelligent call routing and next-best-action • Automated quality assurance and sentiment analytics • Workforce optimization and forecasting augmentation • Post-call summarization and case documentation automation This leader ensures solutions are secure, compliant, ethical, and performant at scale-while establishing reusable engineering patterns that accelerate AI adoption across all Care Center lines of business. The role requires a rare combination of technical acumen, strategic agility, and executive presence. A leader who can earn credibility with engineers and inspire confidence from business Executives. Strategic Impact This role directly influences the TD&O Wholesale Division objectives and key results, including: • Teammate capacity unlocked through automation and AI-assisted work • Number of agentic automation use cases deployed and in production • Benefit realization: efficiency gained, cost savings, and capacity relief for delivered use cases • Modern SDLC / GitLab and GitLab Duo adoption across the developer base • Speed and quality of software delivery through AI-enabled engineering practices • Responsible, governed AI adoption aligned to enterprise policy ESSENTIAL DUTIES AND RESPONSIBILITIES Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time. 1. Directs the development and deployment of AI models and data architectures to enhance system accuracy, efficiency, and resilience. 2. Champions cross-functional collaboration to integrate AI solutions into business applications and processes. 3. Oversees experimentation and performance assessment of AI and data initiatives and makes significant improvements on processes or systems to ensure effectiveness. 4. Drives innovation by contributing to intellectual property and advancing AI capabilities within the organization. 5. Manages multiple AI and data teams led by mid- to upper-level Management. 6. Develops and enforces AI and data governance standards aligned with organizational goals and regulatory requirements. 7. Recommends operational plans and strategies with short- to mid-term (0-3 years) impact on job area results. 8. Collaborates with stakeholders to identify real-world problems and apply AI and analytics for actionable insights. Qualifications Required Qualifications The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. 1. Bachelor's degree in Computer Science, Data Science, AI, Software Engineering, or related field. 2. Minimum of 12 years of professional experience in AI and data with progressive management responsibilities. 3. Proven experience managing teams and delivering AI and data-driven solutions at scale. 4. Strong knowledge of AI models, data architectures, and analytics methodologies. 5. Experience with regulatory compliance and risk management in AI and data technologies. Preferred Qualifications Engineering Leadership: 10+ years leading product, platform, or applied AI engineering teams in large-scale, high-availability environments. 1.Technical Expertise: 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), plus a track record of standing up AI intake, prioritization, and governance models across a large, multi-line-of-business organization. Responsible AI & Regulatory Awareness: Demonstrated knowledge of Responsible AI frameworks, model risk governance, and secure data management practices in a regulated financial services environment. Communication & Influence: Ability to build credibility with engineers while influencing Wholesale executives and delivery leaders. Education: Bachelor's degree in computer science, Engineering, Data Science, or related field (advanced degree preferred) or equivalent experience