Audit Director – AI Technical Enablement

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Working at Citi is far more than just a job. A career with us means joining a team of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview

Whether you’re at the start of your career or looking to discover your next adventure, your story begins here.  At Citi, you’ll have the opportunity to expand your skills and make a difference at one of the world’s most global banks.  We’re fully committed to supporting your growth and development from the start with extensive on-the-job training and exposure to senior leaders, as well as more traditional learning.  You’ll also have the chance to give back and make a positive impact where we live and work through volunteerism.

The AI Assurance Tooling & Execution team are responsible for shaping how Internal Audit leverages AI/GenAI to enhance assurance delivery by developing, prototyping, and integrating AI/GenAI tools into execution. The primary focus involves working with assurance delivery teams to identify, implement, and drive the adoption of specific AI-enabled assurance tests, thereby strengthening and driving efficiency in audit delivery. Scalable implementations will necessitate extensive collaboration with the Strategy, Innovation and Professional Practices (SIPP) team.

The Audit Director – AI Technical Enablement is a senior level management position, reporting to the Chief Auditor Artificial Intelligence (AI) Assurance Tooling & Execution, responsible for managing a team of audit professionals with an overall objective to accelerate the adoption and effective use of AI/GenAI within Internal Audit's assurance activities, focusing on embedding these technologies into execution, identifying strategic use cases, and building AI expertise across the wider IA function.

This role will primarily focus on driving the end-to-end design, implementation, and scalable adoption of high-impact AI/GenAI solutions for IA assurance activities, including developing proof-of-concepts and prototyping from ideation to industrialization. By harnessing AI to strengthen our assurance capabilities, cultivating increased adoption, implementing rigorous feedback loops and continuously evolving our capabilities, this role will help position Citi IA as the leading IA function in the financial services industry.

What you will do

• Provide strategic guidance, oversight, and direction for the execution of IA’s AI and GenAI tooling strategy, including tool evaluation and platform selection for IA assurance.

• Design and implement high-impact AI/GenAI solutions for specific AI-enabled assurance tests, including prototyping and piloting of GenAI audit accelerators.

• Design proof-of-concept and prototyping for high-impact AI and GenAI enabled assurance tests.

• Partner with AI Business Enablement team and key stakeholders in SIPP to ensure scalable and responsible AI adoption, in accordance with Citi’s AI governance frameworks.

• Implement and track adoption metrics and user feedback to continuously improve the AI/GenAI solution and improve overall user experience.

• Proactively diagnose and dismantle systemic impediments to onboarding and adoption, thereby maximizing time-to-value and enabling scalability.

• Conduct horizon scanning and emerging risk research.

• Act as technical specialists for assurance teams.

• Support the broader teams AI assurance mandate.

• Attract, develop, and retain talent; recommending staffing levels required to fulfil responsibilities effectively while establishing and adhering to talent management processes and compensation and performance management programs.

• Work across IA to maximize the efficiency and effectiveness of resources.

• Provide local site leadership encouraging engagement and collaboration across all IA organizations.

• Support and endorse the Quality Assurance (QA) function of IA, and resolve issues found by QA, improving audit processes and coverage.

• Develop and maintain strong working relationships across other IA teams and Regulators.

• Build trust through proactive and transparent interactions while maintaining strong relationships with regulators aligned to Internal Audit.

• Participate and share relevant knowledge and insight, on an ongoing basis, within and across IA teams, to drive the consistent application of the methodology, consistency of audit opinions, higher efficiency, and improved quality of overall assurance.

What we will need from you

Qualifications

• 15+ experience in a related role.

• Experience in technology architecture, enterprise architecture.

• Experience in AI/GenAI product management and technology system life-cycle management.

• In-depth understanding of AI and machine learning concepts, algorithms and techniques, and AI/ GenAI lifecycle.

• In-depth understanding of technical and system architecture, leading development of conceptual design and working with technical teams around solutioning.

• Strong knowledge of IT governance and control frameworks (e.g. COBIT, NIST, Cybersecurity Framework).

• Knowledge of ML Ops principles and practices, including model deployment, monitoring, explainability, and lifecycle management.

• 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.

• Executive presence and expert in building and maintaining strong open relationships with executive stakeholders, working as a partner, exerting influence and providing credible challenge in a constructive manner.

• Ability to quickly comprehend the full risk implications of complex global issues, escalate to the appropriate level and provide advice and on pragmatic commercial solutions.

• Outstanding performer, open minded, resilient, agile, energetic, self-starter, articulate and empathetic whilst being confident to deliver opinions to bring about positive outcomes.

• Strong leadership skills including a track record of identifying and developing world class talent. 

• Experienced in leading large, dispersed and diverse professional teams.

• Demonstrated success in business, functional and people management.

• Consistently demonstrates clear and concise written and verbal communication.

• Demonstrated ability to remain unbiased in a diverse working environment.

• Effective negotiation skills.

Education

• Bachelor’s degree/University degree in decision science, computer science, data science, finance, accounting or a related field, or equivalent experience.

• Master’s degree preferred.

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

Working at Citi is far more than just a job. A career with us means joining a family of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Take the next step in your career, apply for this role at Citi today

https://jobs.citi.com/dei

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Job Family Group:

Internal Audit

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Job Family:

Audit

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Time Type:

Full time

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Most Relevant Skills

Control Monitoring, Data Analysis, Industry Knowledge, Issue Management, Laws and Regulations, Professional Standards, Risk Management, Root Cause Analysis.

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Other Relevant Skills

AI Governance, AI Systems, Audit Assurance, COBIT, Data Governance, Data Privacy, Data Quality Management, Data Security, Generative AI, Information Technology (IT) Risk Management, Internal Audit Development, Internal Audit Management, IT Governance, Machine Learning (ML), Machine Learning Model Management, Machine Learning Operations, NIST Cybersecurity Framework (CSF), Technology Risk Management.

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