Executive Director – Control Management, Artificial Intelligence Technical Program Head

About the position Wells Fargo is seeking an Executive Director – Artificial Intelligence Technical Program Head to be a senior Control Management leader within the Control Analytics Reporting and Data (CARD) organization, responsible for architecting, governing, and scaling AI‑enabled capabilities across the Risk & Control landscape. This role leads the enterprise AI programs for Control Management that will leverage both COO & Operational Risk organizations that enable prompt‑driven intelligence, agentic AI solutions, and control‑centric transformation, elevating how risks are identified, assessed, monitored, tested, and remediated across all Risk Assessable Units (RAUs). Operating at the intersection of Control Management, AI engineering, and enterprise platforms, this leader translates risk and control intent into scalable AI architectures, ensures responsible AI governance, and drives measurable control effectiveness outcomes. This role combines deep technical credibility with control discipline, capable of modernizing Control Management through AI while maintaining trust, transparency, and regulatory confidence.

Responsibilities

• AI Strategy & Control Enablement Define and execute the AI technical strategy for Control Management, aligned to enterprise Risk & Control frameworks, audit expectations, and regulatory standards. Translate control objectives, risk statements, and testing requirements into AI‑enabled capabilities, including prompt‑driven insights and agent‑based workflows. Partner with Control, Risk, Audit, and Compliance leaders to ensure AI solutions augment risk mitigation and control accountability.
• Prompt Engineering & Intelligence Design Establish enterprise standards for prompt design, validation, reuse, and lifecycle management in control and risk use cases. Enable prompt‑driven control intelligence, including: Risk signal detection Control evidence summarization Policy interpretation and obligation mapping Exception analysis and thematic insights Ensure prompts are auditable, explainable, version‑controlled, and outcome‑aligned.
• Agentic AI & Automation Leadership Lead the design and deployment of agentic AI solutions that autonomously: Monitor control performance Execute control checks Trigger remediation workflows Coordinate multi‑step risk assessments Oversee human‑in‑the‑loop models to ensure appropriate escalation, review, and decision accountability. Drive reuse of agents across RAUs to reduce duplication and improve consistency.
• Technical Program & Platform Leadership Lead cross‑functional technical teams (AI engineers, data engineers, platform specialists, control technologists). Own delivery of AI capabilities across enterprise platforms (e.g., internal AI platforms, data fabrics, analytics stacks). Ensure tight integration with data, identity, security, and model governance frameworks.
• Responsible AI, Risk & Governance Embed Responsible AI principles across all solutions, including fairness, explainability, data lineage, and bias monitoring. Partner with Model Risk Management, Technology Risk, and Audit to ensure: Clear model documentation Control traceability Regulatory defensibility Establish controls over AI itself, including model monitoring, drift detection, and prompt misuse prevention.
• Executive Engagement & Transformation Leadership Serve as a senior technical advisor to Control Management and Risk leadership on AI adoption. Communicate AI value in business‑relevant, control‑outcome language for executives, regulators, and auditors. Champion a culture of innovation with discipline across the Control organization.

Requirements

• 7+ years of Risk Management or Business Controls experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 3+ years of management or leadership experience
• Experience across AI engineering, advanced analytics, or enterprise technology, with senior leadership exposure
• Proven experience delivering AI solutions in regulated financial services environments

Nice-to-haves

• Demonstrated success leading large‑scale technical programs spanning multiple teams and stakeholders
• Deep understanding of Generative AI and LLM architectures, prompt engineering and prompt orchestration, and Agentic AI frameworks and autonomous workflows
• Deep understanding of data platforms, APIs, and enterprise analytics ecosystems
• Strong familiarity with Risk and Control Management concepts, including RAUs, control design, testing, issue management, and audit alignment
• Ability to map AI capabilities directly to control effectiveness and risk reduction outcomes
• Track record of building high-performing technical teams in complex environments

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