AVP, AI Enterprise Architecture (Onsite)
About The Position
TM Floyd & Company is seeking an AVP, AI Enterprise Architecture for an onsite role in Chattanooga, Tennessee; Atlanta, Georgia; Portland, Maine; or Columbia, South Carolina. This seasoned enterprise architect will define and evolve the enterprise AI architecture strategy and standards, align AI capabilities with business outcomes and priorities, and help industrialize AI capabilities at scale, primarily using cloud-based and hyperscaler capabilities. The role spans architecture, delivery, governance, risk, and organizational adoption of AI solutions. The AVP will establish scalable, modular, secure agentic AI solutions, reference architectures, reusable patterns, enterprise platforms, and technology roadmaps. They will guide tool and platform selection, evaluate foundation models, and oversee model training, validation, deployment, monitoring, and continuous improvement. The role also contributes directly to AI governance and enterprise standards, ensuring responsible AI practices and compliance with relevant regulatory requirements. Working across business, product, technology, data, risk, legal, and compliance teams, the AVP translates strategy into execution, supports AI business cases, defines outcomes and success metrics, and helps manage AI-specific risks. The role includes influencing senior leaders and mentoring architects and technical leaders while championing disciplined architecture practices and continuous improvement.
Requirements
- 15 years of experience in enterprise architecture, including significant experience designing and implementing enterprise AI/ML platforms and solutions.
- Deep knowledge of AI/ML frameworks, cloud AI services such as 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 such as CI/CD and MLOps.
- Demonstrable experience delivering complex software systems as an engineer and architect.
- Ability to communicate complex technical concepts to technical and business audiences.
- Strategic thinking, strong problem-solving skills, and analytical ability.
- Ability to collaborate and influence across complex organizations.
- Curiosity about emerging technologies and a forward-looking perspective.
- Outcome-driven approach focused on measurable business impact.
- Bachelor's degree required.
Nice To Haves
- Advanced degree preferred.
Responsibilities
- Define and evolve the enterprise AI architecture strategy and standards.
- Represent enterprise architecture on AI governance committees and contribute to governance frameworks and enterprise standards.
- Ensure enterprise AI capabilities align with 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 using cloud-based or hyperscaler capabilities.
- Align AI architecture with enterprise capabilities and technology roadmaps.
- Evaluate emerging technologies and guide tool and platform selection for cost-effective, future-ready solutions.
- Maintain and update enterprise AI platform roadmaps as technology and industry capabilities evolve.
- Ensure delivery teams consistently adopt architecture standards.
- Lead architecture governance, compliance, and quality, including design-time and runtime performance.
- Influence senior leaders and drive alignment across stakeholders.
- Partner with business, product, and technology leaders to translate strategy into execution.
- Guide and mentor architects and technical leaders and champion disciplined architecture practices.
- Drive continuous improvement using lessons from implementation and solution delivery.
- Define business outcomes, use cases, and success metrics, and support AI business cases.
- Partner with the enterprise data team to ensure availability, governance, and compliance of data required for AI solutions.
- Lead evaluation and selection of foundation models, including LLMs, based on business fit and cost.
- Oversee model training, validation, and risk assessment, including assessment of bias and hallucination.
- Define deployment approaches and support enterprise adoption and change management.
- Establish monitoring frameworks for performance, drift, and continuous improvement.
- Ensure alignment with responsible AI principles, including fairness, transparency, and accountability, and with regulatory requirements.
- Partner with risk, legal, and compliance teams to mitigate AI-specific risks such as bias, model drift, and data leakage.
- Establish clear roles, responsibilities, and oversight mechanisms for AI solutions.
Benefits
- A generous array of benefits, depending on the length of assignment.
- Referral bonus of up to $1,000.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
