Responsible AI Governance Specialist

This is a remote position.

Responsible AI Governance Specialist

Overview

We are seeking a Responsible AI Governance Specialist to support our Digital Engineering function, ensuring Responsible AI principles are embedded throughout AI-enabled software development lifecycle (SDLC) processes, engineering platforms and product delivery.

Working closely with Engineering, Platform, Product, Privacy, Data Governance and Cyber Security teams, you will provide governance, advisory and compliance support across AI development initiatives. This role is instrumental in helping the organisation develop, deploy and manage AI solutions that are ethical, transparent, secure and compliant with evolving regulatory requirements.

You will play a key role in AI governance, Responsible AI assessments, model evaluations and risk management, helping engineering teams build AI solutions that meet both business objectives and regulatory expectations.

Key Responsibilities

• Develop, maintain and continuously improve AI governance frameworks, policies, standards, procedures and best practices for the development and use of AI systems.
  
• Support Responsible AI assessments and governance reviews to identify, assess and mitigate ethical, legal and operational risks.
  
• Partner with Engineering, Platform and Product teams to embed Responsible AI principles—including transparency, explainability, robustness, accountability and fairness—into AI-enabled SDLC processes and engineering workflows.
  
• Lead and perform AI model evaluations, including:
  
• Fairness and bias testing
  
• Robustness and resilience assessments
  
• Model lineage verification
  
• Model card validation
  
• Documentation and governance reviews
  
• Coordinate governance activities across Engineering, Product, Privacy, Data Governance and Security functions to ensure consistent application of AI governance standards.
  
• Evaluate third-party AI tools, foundation models and AI-enabled solutions against Responsible AI and regulatory requirements.
  
• Support supplier and supply chain assessments where external AI technologies are incorporated into engineering platforms and development workflows.
  
• Provide expert guidance to senior stakeholders on ethical, safe and compliant AI development, with a particular focus on engineering platforms, AI-enabled software delivery and operational risk.
  
• Monitor emerging AI legislation, standards and industry best practices, helping ensure ongoing compliance with an evolving regulatory landscape.
  

Required Skills & Experience

• Minimum of 2 years' experience in AI Governance, Responsible AI, AI Ethics, AI Risk, AI Compliance, AI Engineering or a related discipline.
  
• Strong understanding of Responsible AI principles, AI ethics and governance frameworks.
  
• Good working knowledge of GDPR and data protection requirements.
  
• Understanding of the EU AI Act and broader AI regulatory developments, with the ability to interpret and apply evolving legislation.
  
• Experience supporting AI governance, model risk management or AI assurance activities is highly desirable.
  
• Relevant degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Law, Ethics, Social Sciences or a related discipline.
  
• Excellent communication and stakeholder management skills, with the ability to engage both technical and non-technical audiences.
  
• Confident presenting recommendations and governance outcomes to senior stakeholders.
  
• Comfortable working within a complex, matrixed organisation and collaborating across multiple technical and business teams.
  

Desirable Experience

• Experience working within software engineering or digital product development environments.
  
• Familiarity with AI model lifecycle management, MLOps or AI-enabled SDLC practices.
  
• Knowledge of AI governance frameworks such as NIST AI RMF, ISO/IEC 42001, ISO 23894 or similar.
  
• Experience assessing third-party AI vendors or AI-enabled SaaS platforms.
  
• Understanding of model explainability, bias detection, AI assurance or AI risk assessment methodologies.