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The AI Assurance Tooling & Execution team is responsible for integrating AI/GenAI tools into audit execution to enhance efficiency and strengthen assurance delivery. The role supports strategic and operational aspects of GenAI assurance tooling, collaborating with audit teams and executing projects aligned with business priorities.
Job Responsibility:
Support the execution and operationalization of IA’s GenAI tooling strategy, including tool evaluation and platform selection for IA Assurance
Manage assessment to facilitate evidence-based build versus buy decisions on high-impact AI/Gen AI solutions for AI assurance tests
Drive collaborative efforts with IA Business/Function teams to implement and embed AI/GenAI solutions, ensuring integration, user adoption, and demonstrable value
Manage key programs and projects for AI/Gen AI initiatives, ensuring timely delivery, adherence to scope, and attainment of required quality standards
Contribute to the strategic optimization of resource allocation and operational capacity for AI/GenAI initiatives, ensuring efficient use of talent and technology
Partners with AI Technical Enablement team to deliver solutions on time, within scope, and to required quality standards
Partner with Directors and Managing Directors to develop approaches for addressing broader corporate emerging issues
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets.
Requirements:
Previous experience in a related role including risk and control experience
Experience of technology enabled change, system rollout and business engagement management in capacity of business relationship management
Experience of enterprise architecture and integration of AI/GenAI into complex and regulated business processes
Sound understanding of AI and machine learning concepts, algorithms and techniques, and AI/GenAI lifecycle
Good knowledge of IT governance and control frameworks (e.g. COBIT, NIST, Cybersecurity Framework)
Familiarity with leading cloud-based AI/ML platforms and their associated governance, security, and deployment best practices
Understanding of security vulnerabilities and risks specific to AI/ML systems, including adversarial attacks and data privacy considerations
Familiarity with data governance principles, data quality management and data security practices
Related certifications such as Certified Information Systems (CISA), Certified Internal Auditor (CIA), Certified in Risk and Information Systems (CRISC) or similar
AI-related certifications are a plus
Demonstrated successful experience in business, functional and people management
Proven ability to execute concurrently on a portfolio of high quality deliverables according to strict timetables
Demonstrated ability to implement continuous improvement and innovation in audit tools and techniques
Consistently demonstrates clear and concise written and verbal communication
Demonstrated ability to remain unbiased in a diverse working environment
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