In-Business Risk 1LOD Sr. Group Manager - C15 - HEREDIA
Citi · Costa Rica · 5d ago
Introduction:
The U.S. Consumer Cards (USCC) AI BRCL provides an independent oversight, review, and approval of Artificial Intelligence (AI) Use Cases (UCs) and AI Assets (Preset, Generative AI Component, or Agent AI) including independent review of AI risk tiering, pre-production testing results, post-production monitoring and AI Asset decommissioning and retirement processes.
Through strong partnership with the USCC AI Accountable Executive and AI Sponsor(s), AI BRCL is responsible to drive controls implementation to mitigate risks associated with AI UCs and AI Assets, in line with Citi AI framework and applicable laws, rules and regulations. AI BRCL is responsible for fostering an environment of continuous improvements and accountability for each AI UCs and AI Asset in their lifecycle. AI BRCL maintains sufficient organizational and operational independence from AI Use Case Sponsors and AI Lead to provide objective review, challenge, escalation, and approval within delegated authority.
Key Responsibilities
Governance and Oversight:
- Exercise delegated approval authority for eligible AI UCs and AI Assets based on comprehensive risk and controls adequacy assessments. For higher-risk / high impact AI UCs, provide the required 1LOD sign-off before routing to the Second Line of Defense (2LOD)
- Provide effective oversight into the AI change management process, including the review and approval of change requests and templates prior to implementation. Escalate to Model Risk Management or other relevant parties when necessary
- Maintain independent oversight and challenge on monitoring results including AI UC / AI Asset performance, risk indicators, and control effectiveness to ensure that the AI UC / AI Asset is operating within its approved parameters and boundaries
- Escalate material control failures, performance breaches, unapproved activity, or operation outside approved parameters promptly to the appropriate governance and risk management teams. This includes AI UC / AI Asset-level issues, portfolio-level risk exposure, and disagreements on risk ratings related to non-compliant AI UCs / AI Assets. Support and coordinate restriction, remediation, or suspension decisions when required
- Review and disposition high-complexity prompt alerts generated by AI monitoring systems, escalating to Model Risk Management or other relevant parties as necessary
- Contribute and support establishment of the business/functions AI risk appetite and thresholds
- Provide guidance on the controls design for AI UC/AI Asset
Risk Assessment & Controls Oversight:
- Review and confirm the accuracy and completion of required risk tier assessments for the AI UCs /AI Assets. Any dispute in risk tiering must be resolved before proceeding to development phase
- Conduct and document a risk-based review and credible challenge of pre-release testing results, control design, residual risk, and approval conclusions — including pre- and post-launch conditions, adequacy of guardrails, and mitigating strategies for AI UCs and AI Assets — to ensure all development requirements are met prior to approving deployment to production
- Assess the impact of new AI UC / AI Asset on existing business processes and controls and drive required controls implementation to support AI UC /AI Asset in its lifecycle. Ensure material changes in use, scope, technology, autonomy, data, regulatory impact or risk profile are assessed and routed for any required reapproval before implementation.
- Evaluate impact of AI UC / AI Asset on third party(es) to detect any undisclosed AI Usage and escalate as necessary
- Confirm that require inventory, approval, testing, control and monitoring records are complete, accurate, and maintained throughout the AI lifecycle.
- Partner with the Chief Technology Office (CTO) and Chief Data Office (CDO) to ensure AI-related processes and controls are adequately designed.
Leadership & Stakeholder Management:
- Engage Legal, Compliance, Controls, Technology, Data, Risk Management, HR and other relevant subject matter experts, as appropriate to promote consistent application of AI policies, standards, and frameworks
- Maintain clear and distinct accountability from AI Lead and AI UC Sponsor while partnering closely to support effective AI Risk and Control Management
- Provide substantive, analytical challenges to the AI UC / AI Asset Sponsors on risk ratings, controls adequacy including guardrails, and risk appetite and relevant thresholds at business and portfolio levels
- Confirm USCC AI UC /AI Asset proposals are aligned with Citi’s broader AI strategy, risk appetite, and AI Ethical Principles
- Oversee and coordinate escalation with 2LOD regarding non-compliant AI UCs / AI Assets
- Communicate complex AI risk concepts effectively to diverse audiences, ranging from technical teams to senior governance committees
- Build and maintain strong working relationships with Business/Function AI Lead and AI UC Sponsors including Enterprise Risk Management, Model Risk Management, Cyber Risk and Independent Compliance Risk Management
- Provide regular updates on the AI risk landscape, control effectiveness, and key escalations within the portfolio to Business/Functions Head of Controls.
Qualifications:
Professional Experience & Education:
- Bachelor's/University degree. Master’s degree is preferred
- 15+ years of experience in a related field, with extensive experience in business and functional management within a large-scale, global organization
- Demonstrated ability to lead complex, preferably AI-oriented implementation and/or business re-engineering initiatives from conception to completion
- Strong experience in driving significant change and control-driven implementation initiatives, with measurable business impact
- Broad and comprehensive knowledge of banking operations, controls, and the associated regulatory landscape
- 8+ years of managerial experience in large financial organizations across multiple disciplines.
Technical & Risk Expertise:
- Sound understanding of AI/ML models and their associated risks and controls, particularly for Generative and Agentic AI, and their associated risks throughout the lifecycle (e.g., to drive appropriate controls to manage hallucination, model drift, bias, autonomy risks)
- Working knowledge of AI governance frameworks, risk management policies, and the full AI Use Case and AI Asset lifecycle is essential
- Ability to assess and classify AI risk levels across the full lifecycle – development, pre-production testing, production monitoring, ongoing monitoring and decommissioning – in line with enterprise frameworks
- Exceptional analytical rigor to evaluate complex AI systems, understand interdependencies, and interpret performance data
- Proficiency in AI risks, including Third Party Risk Management, Cyber Risk, Model Risk, Data Governance and Technology Risk.
- Knowledge of applicable AI laws, regulations and industry frameworks (e.g.: EU AI Act, NIST AI RMF)
- Expertise in process analysis, performance metrics, and data-driven decision-making
- Proficient in review and evaluation of process designs, and identify adversarial risks and dispositions in accordance with Citi frameworks and applicable AI regulations
- Technical knowledge to review and credibly challenge pre-release testing results, model performance metrics, KPIs, drift detection, fairness metrics and explainability outputs.
Leadership & Soft Skills:
- Strong sense of accountability, independence of judgment, and a proactive risk orientation. Must possess strong ethical judgment in upholding Citi's AI Ethical Principles and Code of Conduct
- Exceptional ability to influence and engage in a consultative mode with senior stakeholders across business, operations, technology, and compliance
- Excellent communication and interpersonal skills, with the ability to articulate complex technical concepts to non-technical audiences
- Strategic, results-oriented mindset with a strong sense of accountability
- Strong analytical and problem-solving skills, with the ability to navigate ambiguity and make sound judgments.
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Job Family Group:
Risk Management------------------------------------------------------
Job Family:
In-Business Risk------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Most Relevant Skills
Analytical Thinking, Controls Lifecycle, Credible Challenge, Governance, Policy, Procedure, and Regulation, Risk Management Lifecycle.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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