Tech Risk Manager

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Technology Risk Manager - AI Governance

As part of EY GDS Assurance – Technology Risk Team, as Manager, you’ll lead Technology Risk client engagements and internal projects focused on AI Governance and Responsible AI, managing engagement teams, client relationships, project delivery, risks, and quality of deliverables. You’ll coach team members and foster a collaborative and positive learning culture.

You’ll help clients navigate the evolving AI and Generative AI landscape by leading the design and implementation of AI governance frameworks, policies, risk management practices, and compliance controls. You will work closely with senior stakeholders to establish AI governance operating models, risk assessments, lifecycle controls, regulatory compliance, and responsible AI practices, enabling the secure, ethical, and compliant adoption of AI technologies.

The opportunity

We’re looking for professionals with at least 8+ years of experience, a strong understanding of technology and data, and proven delivery capabilities. This is a fantastic opportunity to join a leading firm and be instrumental in the growth of a new service offering, as well as be part of the growing Technology Risk team.

Skills and Summary of Accountabilities

Lead client-facing engagements and cross-functional collaboration with internal audits, IT security and business stakeholders to assess control effectiveness and facilitate remediation activities.

Preferred knowledge/understanding of experience in IT Controls, Risk and Compliance.

Design IT Risk Controls framework such as IT SOX.

Testing of internal controls such as IT general controls, IT application controls, IPE related controls, interface controls etc.

Lead the design, implementation and continuous improvement of enterprise AI Governance frameworks, policies, standards, controls and operating models to enable responsible, ethical, secure and compliant adoption of AI.

Lead and review AI risk assessments covering bias and fairness, explainability, transparency, privacy, security, model risk, data risk, hallucination and other risks associated with Machine Learning, Generative AI, LLM and Agentic AI solutions.

Oversee AI lifecycle governance, including AI use-case intake, risk classification, approval workflows, Human-in-the-Loop (HITL) controls, governance checkpoints, change/release governance and ongoing monitoring across development, deployment and post-production stages.

Establish and oversee AI inventories, model registers, risk classifications and governance documentation, ensuring appropriate ownership, accountability, traceability and evidence of governance decisions.

Lead collaboration with Data Science, Engineering, Legal, Risk, Compliance, Cybersecurity, and business teams to embed governance into AI development and deployment processes.

Manage AI assurance, audit and compliance reviews, including control assessments, governance evidence, findings, remediation tracking, risk acceptance and validation of remediation closure. Integrate AI Governance with broader IT Risk, Controls and Compliance frameworks where applicable.

Oversee AI risk indicators, model performance, control effectiveness, governance KPIs/KRIs and executive dashboards, escalating material risks and providing clear governance reporting to senior stakeholders.

Provide strategic direction across Data Governance, Data Quality, Metadata Management, Data Lineage and Model Governance, ensuring the underlying data and model governance capabilities appropriately support enterprise AI and Responsible AI requirements.

Lead implementation of Human-in-the-Loop (HITL) controls, AI approval workflows, and governance checkpoints to ensure responsible AI deployment.

Guide adoption of governance capabilities across relevant cloud, data and AI platforms, and drive governance awareness, training and change management to embed Responsible AI practices across the organisation.

To qualify for the role, you must have

8+ years of relevant experience across AI Governance, Model Governance, Technology Risk, AI Risk Management, Data Governance, Responsible AI or Compliance, with experience leading client engagements and cross-functional teams.

Strong understanding of Responsible AI principles, AI Governance frameworks, AI/ML lifecycle governance, AI risk management and control frameworks and their application within enterprise environments.

Knowledge of AI regulations and standards such as ISO/IEC 42001, NIST AI RMF, EU AI Act, and GDPR to advise stakeholders on compliance.

Experience leading AI risk assessments, governance reviews, control assessments, AI assurance, remediation and compliance reporting, including risks associated with Machine Learning, Generative AI, LLMs and Agentic AI.

Experience with AI inventories/model registers, AI risk classification, Human-in-the-Loop controls, approval workflows, lifecycle governance and ongoing AI monitoring.

Familiarity with cloud, AI and data platforms such as Azure AI, Azure OpenAI, Microsoft Fabric, Databricks, AWS or Google Cloud, and governance/GRC platforms used to support control monitoring and complian.

Experience managing GRC processes, audit, compliance, change management, and release governance.

Preferred experience in SQL and Python for analytics, control validation and governance reporting, along with tools such as Jira, Confluence, Azure DevOps, SharePoint or ServiceNow.

Preferred experience with Generative AI Governance, LLM Governance, Agentic AI Governance and/or Model Risk Management (MRM).

Ability to oversee development of governance metrics, dashboards, and executive reporting to support senior stakeholder decisions.

Strong client engagement, leadership and stakeholder-management skills, with the ability to facilitate governance forums, communicate AI risks to senior stakeholders and translate technical, regulatory and risk considerations into practical governance requirements.

Ideally, You'll Also Have

• A bachelor’s degree or higher in Computer Science, Information Systems, Data Science, Information Management, Risk Management, Engineering, or a related discipline. A master’s degree would be an added advantage.
• Relevant certifications, such as AIGP, AI – 500, AB-731, AB-620, CDMP, ISO 8000, or Microsoft Purview, would be an added advantage.
• Excellent communication and stakeholder management skills to influence leaders and align business and technology on governance priorities and risks.
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