Head of AI Enablement – Protection Services

Head of AI Enablement

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If you have a disability and need assistance with the application, you can request a reasonable accommodation by sending an e‑mail to the accommodation requests only contact; other inquiries will not receive a response. Regular or Temporary:
Regular. Language Fluency:
English (Required).

Work Shift:

1st shift (United States of America).

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.

• Translate complex business requirements into engineered AI and GenAI solutions that deliver measurable business outcomes.
• Architect and lead the development of LLM‑based, agentic, and machine‑learning systems that integrate with enterprise data and technology platforms.
• Guide engineering teams in model development, fine‑tuning, and deployment, ensuring performance, security, and compliance.
• Build reusable frameworks, APIs, and components to accelerate AI adoption across product lines.
• Partner 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.
• Serve as a trusted engineering partner to business executives, translating strategic goals into technical blueprints.
• Foster a builder culture rooted in experimentation, delivery, and responsible innovation.
• Establish and enforce AI engineering standards—including model observability, version control, and performance telemetry—in partnership with Enterprise Architecture and the Policy, Standards, Practices Governance team.
• Stay ahead of emerging AI technologies, tools, and frameworks; continuously assess opportunities to integrate frontier capabilities.

• Technical Expertise:
  Proven experience designing, deploying, and maintaining AI or GenAI systems in production—such as LLM‑based solutions, agentic architectures, or advanced ML pipelines.
• Engineering Leadership: 10 years leading product, platform, or applied AI engineering teams in high‑scale environments (e.g., cloud, SaaS, fintech, or large‑scale enterprise systems).
• Architectural Fluency:
  Deep understanding of modern AI infrastructure, including vector databases, model orchestration, RAG pipelines, and MLOps/Dev Ops 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 frameworks, model risk governance, and secure data management practices in regulated industries.
• Communication and Influence:
  Ability to earn trust across senior leadership, from CIOs to product executives, by articulating AI’s value in business terms.
• Education:
  
  Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field (advanced degrees preferred) or equivalent experience.