AI Governance / Ethical AI Specialist

Embed responsible AI practices into the design, development and operation of AI solutions. The role establishes practical controls for risk, transparency, privacy, security, fairness, human oversight and evidence needed for internal governance or regulated use cases.  

• →Assess AI use cases for risk across privacy, bias/fairness, safety, transparency, security and regulatory impact. 
• →Define governance requirements, control checklists, approval gates and evidence expectations for AI projects. 
• →Support model/system documentation including intended use, limitations, data sources, evaluation and monitoring plans. 
• →Review prompts, RAG sources, model outputs and agent behaviors for responsible-AI risks and control gaps. 
• →Partner with architecture and engineering teams to design guardrails, human oversight, logging and escalation mechanisms. 
• →Coordinate risk reviews, issue remediation and audit-ready evidence with legal, compliance, security and product teams. 
• →Track applicable AI standards, regulations and enterprise policy changes and translate them into delivery guidance. 

• Understanding of responsible AI principles: fairness, accountability, transparency, privacy, safety and human oversight. 
• Experience with technology risk, model risk, compliance, data governance, security governance or AI governance. 
• Ability to assess AI/LLM system risks and translate policy into practical engineering controls. 
• Strong documentation, risk analysis, stakeholder management and communication skills. 
• Working understanding of LLM/RAG/agentic systems and their failure modes. 
• Ability to maintain traceable evidence, control matrices and governance decisions. 

• Familiarity with NIST AI RMF, ISO/IEC 42001, EU AI Act concepts or equivalent responsible-AI frameworks. 
• Experience with privacy impact assessments, model cards, red teaming, bias testing or AI safety evaluations. 
• Knowledge of cloud AI governance capabilities and enterprise security controls. 
• Background in regulated sectors such as banking, healthcare, insurance or automotive. 

• Degree in Computer Science, AI, Information Security, Risk, Law/Technology, Data Science or related discipline. 
• Relevant governance, risk, privacy, security or AI certifications are an advantage.