Job Title: Technical Policy Manager - Responsible AI Deployment

Location: London or Cambridge, UK - Hybrid (50% working time at the office)
Employment Type: Full time, Permanent

The Job

You will lead our responsible deployment agenda for AVEVA’s AI software products and for adoption of AI within AVEVA’s operations. Our responsible AI agenda is grounded in a set of core principles: sustainability; accuracy and robustness; human-centricity and fairness; data governance and privacy; transparency and explainability; and accountability.

A key aspect of the role is translating these principles into practical guidance, governance frameworks, learning programmes and deployment standards, helping build a shared understanding of what Responsible AI means for AVEVA, our customers and our stakeholders.

Responsible deployment is core to AVEVA’s Industrial AI agenda, and this role will balance external engagement with internal governance. Externally, you will work with customers, industry bodies, standards organisations, and public sector stakeholders to shape practical governance and accountability approaches for safe, secure, and sustainable AI in industrial operations, across regulated, safety- and mission-critical industrial environments. Internally, you will help to convert those expectations into scalable policies, controls, and decision processes that product and engineering teams can adopt.

You will partner closely with our Product, Enterprise IT, Security, Sustainability, Legal, Risk and Talent and Learning teams, while remaining accountable for responsible deployment in policy design, stakeholder engagement, and enterprise learning enablement.

Key Responsibilities

Responsible AI Governance, Operationalisation & Enablement

• Responsible AI principles and guidance: Translate AVEVA’s Responsible AI Principles into practical guidance, operating procedures, standards and tools that enable consistent application across the AI lifecycle.
• Provide specialist input to the Responsible AI deployment framework: Define and evolve policies, decision rights (RACI), review gates, exception processes, documentation standards and lifecycle controls working within AVEVA’s AI Governance structure. Ensure policy changes and controls are supported by appropriate learning pathways and adoption plans.
• Cross-functional alignment: Coordinate across Security, Risk/Compliance, Sustainability, Legal and commercial teams to maintain a single, coherent governance approach and external message on responsible deployment of AVEVA’s AI working through AVEVA’s existing AI Governance structure.
• Organisational adoption: Lead cross-functional efforts to socialise, communicate and embed AVEVA’s Responsible AI Principles across the organisation, building alignment, shared understanding and consistent adoption across business functions.
• Learning, Enablement & Capacity Building: In partnership with Talent & Learning and Business Function AI Accelerators, define the Responsible AI learning strategy, learning metrics and role-based learning pathways. Translate Responsible AI governance requirements into onboarding content, communications, workshops and scalable digital learning programmes that build awareness, support adoption and reinforce responsible AI practices across the organisation.

Responsible AI Deployment and Adoption

A) Products, Customers & External Engagement

• Customer co-development: Lead strategic engagements with customers to co-design governance and accountability systems for safe, secure and sustainable AI deployment in their operations (risk assessments, control expectations, documentation/evidence packs, monitoring and incident response, accountability boundaries between vendor and operator).
• Public sector & regulator engagement: Support dialogue with government and regulators; translate emerging expectations into clear implications for industrial AI deployment. Support the development and communication of AVEVA’s positions on Responsible AI policy, governance and industrial AI deployment.
• Industry and standards participation: Represent the company in relevant forums (industry working groups, standards bodies and multi-stakeholder initiatives). Contribute practical input on accountability, assurance and deployment patterns grounded in industrial realities.
• External narratives and materials: Develop external-facing guidance (whitepapers, position notes, playbooks and customer assurance packets) to explain how we deploy AI responsibly and how customers can operationalise governance.
• Embed governance into product delivery: Partner with R&D/Portfolio to integrate governance into product delivery systems.
• Responsible deployment patterns: Define and drive responsible deployment requirements (release criteria, human oversight, rollback plans, monitoring and incident response coordination) so governance is real in production, not theoretical.
• Regulated-sector readiness: Ensure auditability, traceability, evidence generation, change control and third-party risk expectations are met for regulated customers.
• Metrics and continuous improvement: Establish KPIs (e.g., deployment readiness, exceptions, time-to-remediate, control coverage) and feed lessons from customer engagements back into internal standards.
• Stakeholder Engagement and Policy Advocacy: Actively engage with industry groups, regulatory bodies and technology partners to advocate for responsible AI practices. Represent the organisation in external forums to share insights, learn from global best practices and contribute to the evolution of Responsible AI governance and policy.