Artificial Intelligence In-Business Controls Sr Lead Analyst Senior Vice President

Artificial Intelligence In-Business Controls Sr Lead Analyst Senior Vice President

The Artificial Intelligence In-Business Controls Sr Lead Analyst Senior Vice President is a strategic professional accountable for multiple activities within COO Controls with a focus on the Office of AI. This role is responsible for embedding robust risk management practices into Citi's AI strategy, ensuring that models, tools, and AI-enabled processes operate safely, ethically, and in compliance with regulatory and internal standards.

Individuals in this role will cover a broad range of in-business/function Artificial Intelligence (AI) impacted risk and control responsibilities.

The ideal candidate has a strong background in Technology Risk, paired with a strong understanding of emerging risks in AI, digitization and automation. Excellent communication skills are required in order to negotiate internally, often at a senior level. Some external communication may be necessary. Accountable for the end results of various In-Business Controls programs.

Risk Identification & Assessment

• Identify, assess, and document risks associated with AI initiatives across the Office of AI.
• Support the review of risk assessments for AI use cases, tools, and model deployments to ensure alignment with enterprise risk appetite and regulatory expectations.
• Partner with Office of AI to evaluate potential control gaps and ensure risks are surfaced early in the development lifecycle.
• Drive execution of the MCA in accordance with the ORM Policy & Framework, as well as applicable Policies, Standards, and Procedures.

Control Design & Implementation

• Support the operationalization of a robust control framework that addresses AI-specific risks.
• Ensure appropriate owned AI-related controls are mapped, tested, and validated.
• Support creation of standardized controls, procedures, and templates to be used for AI strategy.

In-Business Controls (IBC) Execution

• Partner with business leaders to ensure existing IBC processes (MCA, Issue Management) effectively capture relevant AI-related risks and controls.
• Support development of KRIs/KPIs for AI risk monitoring.
• Assist in Issue identification, remediation planning, and sustainable closure for AI-related control breaks.
• Responsible for the coordination and comprehensive management of issues with key stakeholders
• Drive issue quality reviews ensuring compliance with Issue

Governance & Compliance

• Work closely with Legal, Compliance, Model Risk Management, Data Governance, and Technology partners to ensure adherence to internal policies and external regulatory requirements related to AI.
• Engage with subject matter expertise on regulatory trends and emerging industry frameworks for responsible AI.
• Prepare materials for senior leadership, governance forums, audits, and regulatory reviews.
• Responsible for the assessment of activities and processes as per required Policies, Standards and Procedures to strengthen risk management quality.

Cross-Functional Collaboration

• Act as a bridge between AI Strategy, Technology, Operations, and Risk functions to ensure shared understanding of risks and sound execution practices.
• Advise on control implications of new AI capabilities and emerging technologies.

• 10+ years of experience in operational risk management, compliance, audit, or other control-related functions in the financial services industry.
• 7+ years of experience specifically within Risk Management, In-Business Controls (1
  
  LOD), Operational Risk, Compliance, or Technology Risk.
• Mandatory 1
  
  LOD Hands-on
  
  Experience:
  
  Proven track record of hands-on design, implementation, and assessment of risk frameworks and controls within a First Line of Defense (1
  
  LOD) function.
  
  Note:
  
  Pure high-level program management, coordination, or PMO-level oversight of remediation projects is insufficient.
• Cybersecurity & Tech Risk Integration:
  Solid foundational understanding of cybersecurity principles, tech risk mitigation strategies, and experience developing role-based risk training programs.

• Deep Technical Understanding of AI/ML Models:
  Robust knowledge…