Senior AI Productivity Manager

Digital Operations, part of the LSEG Infrastructure & Cloud organisation, is seeking a Senior AI Productivity Manager to lead the AI Productivity Platforms function across the enterprise.

This role will own the enterprise AI platforms , ChatGPT, Claude, Microsoft Copilot and future GenAI capabilities , ensuring secure, scalable, compliant, and value-driven adoption across LSEG. The successful candidate will drive platform enablement, integration, governance, and measurable productivity impact, working closely with business units and technology teams.

As part of this senior leadership role, we are looking for a professional with experience building enterprise AI productivity platform capabilities from the ground up , including operating models, governance frameworks, integration patterns, and value measurement mechanisms. The role requires strong experience across SaaS platform management, API integrations, automation, identity and access management, data protection controls, and enterprise tooling ecosystems.

Key Responsibilities

• Own enterprise strategy, governance, and lifecycle management of AI productivity platforms (ChatGPT, Claude, Microsoft Copilot and future GenAI tools).
• Lead secure enterprise deployment, configuration, identity integration, data protection controls, and policy enforcement.
• Drive connector and MCP integrations between AI platforms and enterprise systems including O365 (Teams, Outlook, SharePoint, OneDrive), Jira, Confluence, Asana, ServiceNow and internal knowledge/workflow platforms.
• Build and lead a high-performing AI Productivity team responsible for platform engineering, integrations, automation, adoption enablement, analytics and value tracking.
• Establish enterprise AI governance frameworks covering responsible use, regulatory compliance, auditability, model risk alignment and vendor risk management.
• Embed AI into business workflows to drive measurable productivity improvements, automation and quality enhancement across engineering, operations and corporate functions.
• Define and track OKRs, SLAs, OLAs and KPIs linked to adoption, time saved, cost optimisation and business impact.
• Partner with CIOs, business leaders, Cyber Security, Risk, Legal and Architecture to ensure safe, scalable and compliant AI enablement.
• Own platform resilience, vendor management, service continuity and cost optimisation across AI tooling.
• Drive continuous improvement, experimentation frameworks and structured scaling of high-impact AI use cases across the enterprise.

Role Requirements

• Proven experience leading enterprise-scale SaaS or digital productivity platform ownership in a complex, regulated environment.
• Deep understanding of MCP (Model Context Protocol) and A2A (Agent-to-Agent), including context modelling, agent roles, communication patterns, and secure integration in enterprise environments.
• Ability to govern, and operationalize MCP and A2A solutions, ensuring scalability, reliability, observability, and alignment with business and compliance requirements.
• Strong understanding of enterprise AI/LLM platforms (ChatGPT Enterprise, Claude Enterprise, Microsoft Copilot) and their security, compliance and operational considerations.
• Demonstrated experience designing secure API integrations across enterprise ecosystems (O365, Jira, Confluence, ServiceNow, workflow and collaboration platforms).
• Strong knowledge of Identity & Access Management, data protection, DLP, governance frameworks and enterprise architecture principles.
• Experience building and scaling technical teams, operating models and governance structures from early-stage capability to enterprise adoption.
• Ability to translate AI capabilities into measurable business value with defined productivity and ROI metrics.
• Strong stakeholder management and executive communication skills with experience influencing senior leadership.
• Experience operating in high-control, risk-aware environments with structured ITSM and change management processes.
• Commercial acumen including vendor management, licensing optimisation and cost governance.
• Strategic mindset with hands-on technical depth and a bias toward execution and measurable outcomes.

Benefits

• Healthcare
• Retirement planning
• Paid volunteering days
• Wellbeing initiatives