AVP, AI Enterprise Architecture

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.
• 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
• Continuously maintain and update the enterprise AI platform roadmaps as technology and industry capabilities evolve
• Ensure consistent adoption of architecture standards across delivery teams
• Lead architecture governance, compliance, and quality (design‑time and runtime performance)
• Influences senior leaders and drives alignment across stakeholders
• Partner with business, product, and technology leaders to translate strategy into execution
• Guide and mentor architects and technical leaders while being a champion of disciplined architecture practices across the organization
• Drive continuous improvement through learnings from implementation and solution delivery
• Define business outcomes, use cases, and success metrics; 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 (LLMs, etc.) based on business fit and cost
• Oversee model training, validation, and risk assessment (e.g., bias, 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 (fairness, transparency, accountability) and regulatory 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

• 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 experience of delivering complex software systems as an engineer and architect
• Proven ability to communicate complex technical concepts to both technical and business audiences
• Experience with standard enterprise architecture modeling practices (Archi Mate and Bizzdesign preferred)
• Strategic thinker with strong problem‑solving and analytical skills
• Collaborative and influential leader across complex organizations
• Curious and forward‑looking on emerging technologies
• Outcome‑driven with focus on measurable business impact

• Bachelor's degree
• Advanced degree (preferred)