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Posted 2 weeks agoAVP, AI Enterprise Architecture
at Unum Group
Atlanta, United StatesOn-site
Responsibilities
- Ensure enterprise AI capabilities are aligned to business outcomes and enterprise priorities Design scalable, modular, and secure agentic AI solutions Establish reference architectures, reusable patterns, and enterprise platforms to industrialize AI capabilities at scale (primarily cloud-based / hyperscaler capabilities) Align AI architecture with enterprise capabilities and technology roadmaps Evaluate emerging technologies and guide tool/platform selection to ensure cost-effective, future-ready solutions
Requirements
- Join us. General Summary: This role is responsible for defining and advancing the enterprise AI architecture strategy assuring scalable, secure, and flexible AI capabilities that enable rapid delivery of business value.
- It serves as the bridge between enterprise architecture strategy and execution, shaping how solutions integrating AI are designed, governed, and deployed across the organization.
- The leader directly contributes to the design and development of enterprise AI platforms, reference architectures, and reusable patterns, while ensuring our AI architecture & technology decisions align to Unum Group’s business strategy and long-term value.
- This role acts as a thought leader and orchestrator, partnering across technology and business teams to integrate AI into the enterprise in a disciplined, sustainable, and responsible way.
- Responsibilities Define and evolve the enterprise AI architecture strategy and standards Be the enterprise architecture representative in AI governance committees and directly contribute to governance frameworks and enterprise standards.
- requirements Partner with risk, legal, and compliance teams to mitigate AI-specific risks (e.g., bias, model drift, data leakage) Establish clear roles, responsibilities, and oversight mechanisms for AI solutions Job Specifications Bachelor’s degree required; advanced degree preferred 15+ years of
- experience in enterprise architecture with significant
- experience designing and implementing enterprise AI/ML platforms and solutions Deep knowledge of AI/ML frameworks, cloud AI services (e.g., AWS), and modern data technologies
- Experience with foundation models, prompt engineering, RAG architectures, and agentic AI patterns Strong understanding of AI risks, governance frameworks, and regulatory considerations Familiarity with Agile/Lean delivery and modern engineering practices (e.g., CI/CD, MLOps) Demonstrable