Frontier Trust & Governance Lead

Full Job Description

Strategy & Transformation: Assess governance and security maturity, identify capability gaps, and develop governance transformation roadmaps. Advise customers on governance maturity progression from foundational AI governance through autonomous and ecosystem-scale governance. Design the AI Governance Operating Model including governance forums, stakeholder structures, decision rights, accountability models, and executive oversight mechanisms. Establish Responsible AI, risk, security, privacy, and compliance frameworks, including policies, standards, control requirements, and governance guardrails that enable safe AI adoption at scale. Design and operationalize AI and agent governance across the solution lifecycle, including intake, assessment, approval, deployment, runtime monitoring, change management, retirement, and ongoing oversight. Establish governance observability and assurance capabilities, including governance metrics, executive reporting, auditability, compliance evidence, risk monitoring, and continuous assurance mechanisms. Partner with customer executives, risk, compliance, legal, security, and business stakeholders to stand up governance councils, manage emerging regulatory requirements, and address evolving challenges associated with AI and autonomous systems. The customer has an adopted AI Governance Operating Model with clear ownership, accountability, decision rights, and executive oversight across AI, agents, data, and autonomous systems. AI and agent solutions move from experimentation to production quickly and safely because governance, security, privacy, compliance, and Responsible AI controls are embedded by design rather than applied afterwards. Customer data, identities, infrastructure, models, and agent ecosystems are protected through enterprise-scale governance, security, access management, threat protection, monitoring, and policy enforcement. Autonomous systems operate within defined security, permissioning, accountability, escalation, and human-oversight boundaries, enabling safe adoption of agentic operating models. Executives have clear visibility into AI risk, governance effectiveness, security posture, compliance status, and operational performance through measurable assurance and reporting mechanisms. Governance and security capabilities are embedded into business operations and scale consistently across AI solutions, business functions, and regulatory environments. The organisation can confidently govern and secure increasingly autonomous AI systems and multi-agent ecosystems without requiring significant redesign of governance or security structures. The customer becomes self-sufficient in governing, securing, and continuously evolving its Trust & Governance capability as a strategic enterprise operating capability Bachelor's degree in Information Security, Computer Science, Risk Management or a related field, AND 10+ years of experience in risk management, compliance, security, or governance; OR Master's Degree in a relevant field AND 8+ years of such experience; OR equivalent experience. Proven experience designing and operationalising enterprise-scale AI governance, security, risk, and compliance capabilities, including governance operating models, accountability frameworks, and executive oversight structures for technology transformation initiatives. Deep understanding of AI, agentic AI, and autonomous system risks, including model, data, identity, security, privacy, compliance, resilience, and Responsible AI considerations. Experience balancing innovation velocity with appropriate governance and organizational risk tolerance. Experience designing governance and security guardrails for AI solutions, including identity and access management, data protection, threat protection, monitoring, auditability, and policy enforcement. Executive communication skills, including board-level risk reporting. Experience leading cross-functional governance programmes involving business, legal, compliance, security, technology, and executive stakeholders. Ability to work directly with senior stakeholders to define policy and operationalize controls. Experience defining governance operating models, decision-rights frameworks, ownership structures, governance councils, and executive reporting mechanisms. Executive presence and stakeholder influence, with the credibility to advise C-level, risk, security, legal, and business leaders and align them on governance, security, and AI strategy. Ability to translate complex AI risks, options, and trade-offs into concise executive briefings, decision papers, and points of view that enable informed decisions. Experience with AI/ML governance frameworks and Responsible AI programs. Background in regulated industries such as Financial Services, Healthcare, or Government. Experience governing AI agents, Copilots, and autonomous systems at enterprise scale Experience working with regulators, auditors, governance councils, and executive oversight bodies to operationalise AI governance and compliance. Experience transferring governance practice and tooling to a client's own risk and compliance function.

Verified from public schema.org JobPosting structured data on the official source page. The complete published description, responsibilities, requirements and benefits were normalized when present; unstated facts were not inferred.