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LSEG

Global financial market infrastructure and data

Senior AI Productivity Manager

Enterprise ApplicationsConfirmed live in the last 24 hours
Full-timeBucharest, RomaniaNo salary listedIn-person

About the Job

Requirements

  • Proven experience leading enterprise-scale SaaS or digital productivity platform ownership in a complex, regulated environment.
  • Deep understanding of Model Context Protocol and Agent-to-Agent concepts, including context modelling, agent roles, communication patterns, and secure integration in enterprise environments.
  • Ability to govern and operationalize Model Context Protocol and Agent-to-Agent solutions, ensuring scalability, reliability, observability, and alignment with business and compliance requirements.
  • Strong understanding of enterprise AI and large language model platforms, including ChatGPT Enterprise, Claude Enterprise, and Microsoft Copilot, and their security, compliance, and operational considerations.
  • Demonstrated experience designing secure application programming interface integrations across enterprise ecosystems, including O365, Jira, Confluence, ServiceNow, workflow, and collaboration platforms.
  • Strong knowledge of Identity and Access Management, data protection, data loss prevention, 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 return-on-investment metrics.
  • Experience operating in high-control, risk-aware environments with structured IT service management 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.

Responsibilities

  • Own enterprise strategy, governance, and lifecycle management of AI productivity platforms, including ChatGPT, Claude, Microsoft Copilot, and future generative AI tools.
  • Lead secure enterprise deployment, configuration, identity integration, data protection controls, and policy enforcement.
  • Drive connector and Model Context Protocol integrations between AI platforms and enterprise systems, including O365 (Teams, Outlook, SharePoint, OneDrive), Jira, Confluence, Asana, ServiceNow, and internal knowledge and 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 objectives and key results, service-level agreements, operational-level agreements, and key performance indicators linked to adoption, time saved, cost optimisation, and business impact.
  • Partner with chief information officers, 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.
  • Lead a regional squad of AI developers, partnering globally to establish a consistent enterprise AI productivity enablement model, drive adoption, and ensure safe, governed use of AI platforms.

About the Company

LSEG

Global financial market infrastructure and data

LSEG provides global financial market infrastructure and data across the full value chain. It delivers data, analytics, and risk-management tools, benchmarks via FTSE Russell, regulatory and financial crime risk services, and trading, clearing, and settlement through its Capital Markets and Post Trade divisions, typically accessed via subscriptions, licensing, and fees. The company differentiates itself by offering an integrated, end-to-end platform that covers pre-trade data and analytics to post-trade processing with a broad, global footprint. Its goal is to grow over the long term by leveraging its diversified portfolio and international reach to create value for shareholders and customers.

Company size
10,001+
Company stage
IPO
Headquarters
London, United Kingdom
Founded
1801

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