AI Ethics & Governance Specialist

Role Overview 

Lead responsible AI initiatives by ensuring ethical deployment, regulatory compliance, risk management, and model explainability across AI systems. Champion trustworthy and transparent AI practices.  

Responsibilities 

• Develop and implement responsible AI frameworks, policies, and governance structures 
• Conduct ethical assessments and risk evaluations for AI systems and models 
• Ensure compliance with AI regulations (GDPR, AI Act, CCPA, industry standards) 
• Perform bias audits, fairness testing, and discrimination risk assessments 
• Implement model explainability and interpretability solutions (SHAP, LIME, attention visualization) 
• Create documentation and transparency reports for AI systems 
• Collaborate with legal, compliance, and technical teams on AI governance 
• Train teams on responsible AI practices and ethical considerations 
• Monitor emerging AI regulations and update policies accordingly 

Requirements 

• Bachelor's degree in Computer Science, Law, Ethics, Public Policy, or related field 
• Strong understanding of responsible AI principles and frameworks 
• Proven experience with AI compliance and regulatory requirements 
• Expertise in risk assessment methodologies for AI systems 
• Hands-on experience with explainability tools and techniques (SHAP, LIME, InterpretML) 
• Knowledge of AI ethics, fairness metrics, and bias mitigation strategies 
• Understanding of ML model development lifecycle and deployment practices 
• Excellent communication skills to explain complex technical concepts to non-technical stakeholders 

Preferred 

• Advanced degree (MS/PhD) in relevant field or law degree with tech focus 
• Experience with AI governance frameworks (NIST AI RMF, ISO/IEC standards, EU AI Act) 
• Familiarity with industry-specific regulations (healthcare HIPAA, finance regulations) 
• Technical background with Python and ML frameworks 
• Experience conducting algorithmic impact assessments 
• Knowledge of privacy-preserving techniques (differential privacy, federated learning) 
• Certifications in AI ethics or governance 
• Experience working with cross-functional and executive teams 

Technical Skills 

• AI explainability tools (SHAP, LIME, Captum, InterpretML) 
• Understanding of ML models and their potential risks 
• Documentation and audit trail management 
• Risk assessment frameworks and methodologies