Bachelor's or Master's degree in relevant fields such as Computer Science or Law.
5+ years of experience in AI governance or technology risk.
Strong understanding of AI, ML, and Generative AI lifecycles.
Experience developing governance frameworks and policies.
Knowledge of AI risk management and regulatory compliance requirements.
Experience collaborating with cross-functional stakeholders, including executives.
Strong analytical, presentation, and documentation skills.
Responsibilities
Assess clients' AI governance maturity and recommend improvement strategies.
Design and implement governance frameworks for the entire AI lifecycle.
Develop policies and control frameworks aligned with regulations.
Conduct AI and model risk assessments to gauge compliance and risks.
Advise on Responsible AI practices including fairness and explainability.
Support documentation and management of AI models and governance artifacts.
Guide on governance processes for Generative AI and other advanced applications.
Benefits
Hybrid work model allowing flexibility between remote and on-site work.
Professional development opportunities through training and workshops.
Engagement with a diverse range of stakeholders including clients and regulatory bodies.
Contribution to the evolving field of AI governance and Responsible AI practices.
Opportunity to influence AI strategy in complex and regulated industries.
Full Job Description
Job Title: AI Governance Consultant
Job Summary
We are seeking an AI Governance Consultant to advise clients and internal stakeholders on establishing and maturing AI governance frameworks that enable the responsible, secure, and compliant adoption of Artificial Intelligence (AI), Machine Learning (ML), and Generative AI solutions. The ideal candidate has expertise in AI governance, risk management, Responsible AI, regulatory compliance, and AI lifecycle management. This role partners with business leaders, AI engineers, data scientists, legal, privacy, cybersecurity, risk, and audit teams to develop governance strategies, policies, and operating models that align AI initiatives with business objectives and regulatory expectations.
Key Responsibilities
Assess clients' AI governance maturity and recommend governance operating models and implementation roadmaps.
Design and implement AI governance frameworks covering the full AI lifecycle, from ideation through retirement.
Develop AI policies, standards, procedures, and control frameworks aligned with business and regulatory requirements.
Conduct AI risk assessments, model risk assessments, and AI impact assessments.
Advise on Responsible AI practices, including fairness, transparency, explainability, accountability, privacy, and human oversight.
Support AI inventory management, model documentation, model cards, data sheets, and governance artifacts.
Guide organizations in implementing governance processes for Generative AI, Large Language Models (LLMs), AI agents, and Retrieval-Augmented Generation (RAG) applications.
Interpret and apply applicable AI, privacy, cybersecurity, and industry regulations to AI initiatives.
Collaborate with legal, compliance, cybersecurity, internal audit, and enterprise risk teams to establish governance controls.
Develop AI governance metrics, reporting dashboards, and executive-level governance reports.
Support internal and external AI audits, regulatory reviews, and compliance assessments.
Deliver workshops, training sessions, and stakeholder awareness programs on AI governance and Responsible AI.
Stay informed about evolving AI regulations, standards, frameworks, and industry best practices.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Information Technology, Data Science, Law, Risk Management, Business Administration, or a related field.
5+ years of experience in AI governance, technology risk, model risk management, compliance, consulting, information security, or data governance.
Strong understanding of AI, machine learning, Generative AI, and AI system lifecycles.
Experience developing governance frameworks, policies, standards, and operating models.
Knowledge of AI risk management, regulatory compliance, and enterprise governance practices.
Experience working with cross-functional stakeholders, including executive leadership.
Strong analytical, documentation, presentation, and consulting skills.
Preferred Qualifications
Experience advising organizations on enterprise AI governance transformations.
Knowledge of Responsible AI, AI ethics, explainability, fairness, and AI safety practices.
Experience with AI model governance, MLOps governance, and AI assurance.
Familiarity with AI evaluation methodologies and AI audit processes.
Experience with cloud governance, data governance, and cybersecurity governance.
Experience supporting highly regulated industries such as banking, healthcare, insurance, telecommunications, energy, or the public sector.
Professional certifications in governance, risk, privacy, cybersecurity, cloud, or AI.
Technical Skills
AI Governance Framework Design
Responsible AI
AI Risk Management
Model Governance
AI Lifecycle Governance
Model Documentation
AI Impact Assessments
Risk Assessment Methodologies
Compliance Management
Governance, Risk, and Compliance (GRC) Platforms
Microsoft Excel
Power BI or Tableau
SQL (preferred)
Python (preferred)
AWS / Azure / Google Cloud Platform (preferred)
Regulatory & Framework Knowledge
AI governance frameworks
Model Risk Management (MRM)
Responsible AI principles
AI transparency and explainability
Data privacy and security principles
AI assurance and audit methodologies
Enterprise risk management
Industry-specific regulatory requirements
Consulting & Soft Skills
Executive stakeholder management
Strategic consulting and advisory
Strong presentation and facilitation skills
Excellent written communication and documentation
Analytical thinking and structured problem-solving
Cross-functional collaboration
Change management and organizational influence
Nice to Have
Experience developing enterprise AI governance operating models
Experience implementing AI governance tooling and workflows
Knowledge of AI vendor risk management and third-party AI assessments
Familiarity with AI policy development, AI ethics committees, and governance boards
Contributions to AI governance thought leadership, standards, or industry working groups
Key Performance Indicators (KPIs)
AI governance framework adoption and maturity
Successful completion of AI risk and impact assessments
Audit and regulatory readiness
Reduction in AI governance and compliance findings
Timely delivery of governance programs and advisory engagements
Stakeholder satisfaction and governance adoption
Quality and completeness of governance documentation
Improvement in Responsible AI compliance across AI initiatives
