Head Of AI Enablement - Truist Protection Services

Head Of Ai Enablement

The head of AI enablement is a senior technology leader responsible for designing and deploying enterprise-grade AI and GenAI solutions across Truist Protection Services. Reporting directly to the Chief Security 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. This role is hands-on and technically deep — blending engineering expertise in LLMs, agentic frameworks, and applied ML with the ability to engage directly with business stakeholders. The ideal candidate has built and deployed AI platforms or intelligent products in a technology-first environment, demonstrating fluency in system design, data architecture, and model integration.

Essential duties and responsibilities include translating complex business requirements into engineered AI and GenAI solutions that deliver measurable business outcomes, architecting and leading the development of LLM-based, agentic, and machine-learning systems that integrate with enterprise data and technology platforms, guiding engineering teams in model development, fine-tuning, and deployment, building reusable frameworks, APIs, and components to accelerate AI adoption across product lines, partnering directly with the TD&O divisional leaders and their engineering, product, and operations teams to identify high-impact use cases and embed AI capabilities into existing workflows, serving as a trusted engineering partner to business executives, translating strategic goals into technical blueprints, fostering a builder culture rooted in experimentation, delivery, and responsible innovation, establishing and enforcing AI engineering standards, staying ahead of emerging AI technologies, tools, and frameworks, and continuously assessing opportunities to integrate frontier capabilities.

Required qualifications include technical expertise, engineering leadership, architectural fluency, applied business translation, ethical and regulatory awareness, communication and influence, and education. Preferred qualifications include prior experience at a technology or product company, hands-on experience with enterprise AI frameworks, demonstrated success establishing AI engineering standards, reusable frameworks, or AI Centers of Excellence, experience delivering GenAI applications for customer engagement, operations, or risk functions in complex organizations, and industry leadership through publications, open-source contributions, or conference presentations.