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TruistHead of AI Enablement
Senior technology leader responsible for AI and GenAI solutions across Wholesale Technology for Truist. Collaborating with business executives and engineering teams to drive measurable value through AI applications.
About the role
- Lead the evaluation and strategic assessment of emerging AI technologies, platforms, and vendor solutions, advising on technical and ethical feasibility
- Design and guide the development of AI capabilities and innovation pilots, translating business goals into AI-enabled solutions
- Define architectural blueprints for integrating AI technologies into IT systems and product platforms, ensuring security, scalability, and alignment with enterprise standards
- Develop frameworks for responsible AI adoption including model evaluation, explainability, privacy, compliance (e.g., EU AI Act), and ethical use
- Partner with product and platform teams to align AI innovations with enterprise technology strategy and business outcomes
- Drive initiatives for AI prototyping, proof-of-concepts (PoCs), and production readiness assessments
- Monitor vendor roadmaps and contribute to the strategy for selecting and onboarding external AI capabilities
- Act as a center of excellence for AI within the IT organization, driving awareness, knowledge sharing, and standardization
- Collaborate with enterprise architects and platform leads to integrate AI tools into data infrastructure, software architecture, and cloud environments
- Perform technical due diligence on third-party AI services and models, ensuring fit-for-purpose and cost-effective solutions
- Continuously improve internal innovation processes and methodologies to increase the speed and quality of AI-driven transformation
Requirements
- Bachelor’s degree or equivalent in Computer Science, Artificial Intelligence, Data Science, or a related field
- Advanced degrees (MSc/PhD) in AI/ML fields preferred
- TOGAF, COBIT, or related enterprise architecture certifications are beneficial
- Certifications in machine learning or cloud-based AI platforms (e.g., AWS Certified Machine Learning Specialty, Google Cloud AI Engineer) are advantageous
- Extensive experience in leading enterprise AI innovation and architecture initiatives
- Proven track record of evaluating, piloting, and operationalizing AI solutions in enterprise environments
- Experience working across multiple industries and large-scale IT organizations
- Hands-on experience in AI/ML development, integration, and lifecycle management
- Familiarity with regulations governing AI use, such as the EU AI Act, and experience in operationalizing compliance measures
Benefits
- Health insurance
- Professional development opportunities
Job title
Job type
Experience level
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Not specified
Degree requirement
Tech skills
Location requirements
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