Chief AI Architect

Key Accountabilities

• Define and execute the AI architecture roadmap for Advice & Wealth Management in partnership and collaboration with other organizations.
• Establish architecture patterns for both traditional ML and generative AI, including deployment and monitoring.
• Help business and product leaders understand how they can leverage AI to solve their business problems.
• Influence enterprise guardrails and standards for responsible AI usage (evaluation, observability, model performance, and risk management).
• Establish repeatable patterns for integrating AI into applications, workflows, and platforms.
• Partner with data architecture to ensure AI‑ready data foundations (quality, governance, lineage).
• Guide teams on build vs. buy vs. partner decisions for AI capabilities and platforms.
• Research emerging AI technologies and patterns; translate into practical recommendations and investment proposals.
• Influence senior leadership on AI strategy, investment priorities, and sequencing.
• Coach and mentor architects and senior engineers in AI architecture and design practices.

• Deep expertise across both traditional ML and generative AI architectures
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• Proven ability to apply AI to real business use cases
  , moving solutions from concept to production.
• Experience designing AI systems that are secure, observable, and scalable
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• Strong understanding of model lifecycle management (training, deployment, monitoring, retraining).
• Experience establishing responsible AI governance and controls
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• Knowledge of AI/ML platforms, cloud‑native patterns, and integration approaches (e.g., MCP, A2A, etc.).
• Ability to influence senior stakeholders and collaborate across business and technology.

• AI capabilities are consistently applied to high‑value business use cases across AWM.
• Clear, reusable AI architecture patterns adopted across teams.
• AI systems operate with strong observability, quality, and governance
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• Business leaders have confidence in AI‑driven decision support and automation.
• AWM is positioned to scale both traditional AI and generative AI capabilities responsibly
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• Defining GenAI and agent‑based architecture patterns (e.g., RAG, orchestration layers, evaluation frameworks).
• Establishing AI observability and monitoring practices across all solutions.
• Driving AI adoption in advice workflows (advisor assist, client engagement, operations automation).
• Creating clear guidance on when and how to use AI vs. traditional approaches
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• Partnering with Data Architecture to ensure AI‑ready data foundations
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• Integrating AI capabilities across multiple Vanguard systems and third‑party platforms
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• Partnering with Enterprise AI & Engineering Platforms organization to shape enterprise AI reference architecture and technology that supports AWMT AI priorities.

Vanguard is not offering visa sponsorship for this position.