AI SME - Responsible AI Framework & Standards

Eaglecliff Recruitment; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Senior AI SME is sought to join a world-leading energy company to implement and advise AI principles across the AI portfolio. The role ensures AI systems are designed, developed, and deployed in alignment with values, regulatory requirements, and Responsible AI principles, enabling safe adoption and business value realization.

Responsibilities include governance integration, education and adoption, and leading AI risk assessments while engaging senior stakeholders and fostering a culture where

Qualifications

• 8-12+ years in AI/ML, data science, AI governance, model risk, or technology risk.
• Experience evaluating AI risks, fairness, transparency, and explain-ability.
• Experience engaging senior stakeholders and influencing enterprise decisions.
• Experience in regulated or complex enterprise environments preferred.

Responsibilities

• Maintain Responsible AI principles and related practices and guidance.
• Work with legal to establish fairness, transparency, explainability, accountability, and human oversight requirements.
• Develop practical controls and assessment criteria for AI use cases.
• Lead Responsible AI reviews for high-risk AI solutions (AI Steward).
• Conduct assessments for bias, fairness, explainability, safety, and unintended consequences.
• Provide recommendations to enable safe deployment.
• Embed Responsible AI controls into lifecycle management and governance workflows.
• Partner with Governance Operations to operationalise Responsible AI requirements.
• Support model approval and risk review processes with AI ERC.
• Act as enterprise Responsible AI thought leader; develop guidance and training materials.
• Promote a culture where Responsible AI enables innovation and adoption.

Skills

Responsible AI

AI governance

AI risk management

Regulatory compliance

Stakeholder engagement

Ethics

Explainability

Job description

Exciting opportunity for a Senior AI SME to join this world leading Energy company and be accountable for implementing and advising AI principles across the company's AI portfolio.

The role ensures AI systems are designed, developed, and deployed in alignment with the company's values, regulatory requirements, and Responsible AI principles, while enabling safe adoption and business value realisation.

Key Accountabilities:

Responsible AI Framework & Standards:

• Maintain Responsible AI principles (along with AI quality & monitoring, discoverability, documentation, AI lineage) related practices and guidance.
• Work with legal to establish requirements for fairness, transparency, explain-ability, accountability, and human oversight.
• Develop practical controls and Responsible AI assessment criteria for AI use cases. AI Risk Assessments
• Lead Responsible AI reviews for high-risk and business-critical AI solutions - aka AI Steward
• Conduct assessments for bias, fairness, explain-ability, safety, and unintended consequences.
• Provide recommendations and mitigation actions to enable safe deployment.

Governance Integration:

• Embed Responsible AI controls AI lifecycle management processes and governance workflows.
• Partner with Governance Operations to operationalise Responsible AI requirements within platforms and tooling.
• Support model approval and risk review processes with AI ERC

Education & Adoption:

• Act as the enterprise Responsible AI thought leader and trusted advisor.
• Develop playbooks, guidance, training, and awareness programs.
• Promote a culture where Responsible AI enables innovation rather than becoming a barrier to adoption.

Experience:

• 8-12+ years in AI/ML, data science, AI governance, model risk, or technology risk.
• Experience evaluating AI risks, fairness, transparency, and explain-ability.
• Experience engaging senior stakeholders and influencing enterprise decisions.
• Experience in regulated or complex enterprise environments preferred.

Expertise:

• Responsible AI and AI ethics
• Fairness, explain-ability, transparency, and AI safety
• AI risk management and governance
• AI/ML lifecycle and model development practices
• Policy interpretation and control design behaviours
• Demonstrates sound judgment and integrity
• Challenges constructively while enabling innovation
• Balances business value with ethical considerations
• Influences through expertise and credibility
• Promotes transparency, accountability, and trust