✦ Luna Orbit — AI & Machine Learning

Head of AI Enablement - TD&O Wholesale

at Truist Financial

📍 4 Locations Unknown Posted March 29, 2026
Type Not Specified
Experience lead
Exp. Years 10+ years
Education Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field (advanced degrees preferred) or equivalent experience.
Category AI & Machine Learning

The Head of AI Enablement leads the design and deployment of enterprise-grade AI and GenAI solutions across Wholesale Technology and Data & Operations, partnering with executives to translate requirements into scalable AI applications. The role blends deep technical depth with strategic leadership to accelerate adoption and ensure governance.

  • Translate business requirements into engineered AI solutions
  • Architect and lead LLM-based systems
  • Guide model development and deployment
  • Build reusable AI frameworks and APIs
  • Partner with Divisional Leaders to identify use cases

Hands-on and strategic leadership in LLM-based solutions, agentic architectures, and ML pipelines; focus on security, ethics, observability, and engineering standards; experience with frontier AI tools and platforms.

The ideal candidate is a seasoned AI leader with 10+ years in engineering AI platforms, strong architectural fluency, and a track record of delivering GenAI solutions in regulated industries. They should excel at bridging business strategy and technical execution with executive presence.

Technical Expertise: Proven experience designingdeployingand maintaining AI or GenAI systems in production-such as LLM-based solutionsagentic architecturesor advanced ML pipelines.Engineering Leadership: 10+ years leading productplatformor applied AI engineering teams in high-scale environments (e.g.cloudSaaSfintechor large-scale enterprise systems).Architectural Fluency: Deep understanding of modern AI infrastructureincluding vector databasesmodel orchestrationRAG pipelinesand MLOps/DevOps integration.Applied Business Translation: Ability to engage directly with business leaders to convert strategic goals into technical blueprints and deliver working solutions.Ethical and Regulatory Awareness: Demonstrated knowledge of Responsible AI frameworksmodel risk governanceand secure data management practices in regulated industries.Communication and Influence: Ability to earn trust across senior leadershipfrom CIOs to product executivesby articulating AI's value in business terms.Education: Bachelor's degree in Computer ScienceEngineeringData Scienceor a related technical field (advanced degrees preferred) or equivalent experience.
Prior experience at a technology or product companyleading AI platform or applied ML development at scale.Hands-on experience with enterprise AI frameworks (Azure OpenAIAWS BedrockLangChainAutoGenCrewAIor similar).Demonstrated success establishing AI engineering standardsreusable frameworksor AI Centers of Excellence.Experience delivering GenAI applications for customer engagementoperationsor risk functions in complex organizations.Industry leadership through publicationsopen-source contributionsor conference presentations.
Designing AI/GenAI systems in productionleading AI engineering teamsarchitectural fluency in AI infra (vector DBsmodel orchestrationMLOps)business translationResponsible AI and secure data management
LLM-based solutionsagentic architecturesmachine learning pipelinesmodel observabilityversion controlperformance telemetrysecurityethicsResponsible AImodel risk governancesecure data managementAI engineering standardsAzure OpenAIAWS BedrockLangChainAutoGenCrewAIMLOpsDevOps integration
executive presencestakeholder managementarchitecture leadershipcommunicationinfluencebuilding cross-functional squads
Industry Banking
Job Function Design and deploy enterprise-grade AI/GenAI solutions across Wholesale TD&O, balancing technical depth with executive strategy.
Role Subtype Head of AI Enablement
Tech Domains Python, Power BI, Tableau, Amazon Web Services, SQL / PostgreSQL, Azure
head of ai enablementtd&o wholesaleai enablementgenaillmagentic architecturesmachine learning pipelinesvector databasesmodel orchestrationrag pipelinesmlopsdevops integrationresponsible aimodel risk governancesecure data managementai engineering standardsazure openaiaws bedrocklangchainautogencrewaistakeholder managementexecutive leadershipmodel observabilityAzure OpenAI
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