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LS
Senior Product Manager (MCP Integrations)
London Stock Exchange · London, United Kingdom
About The Role
Join LSEG's AI team as a Senior Product Manager for MCP Integrations & Agentic Workflows. In this role, you will define the integration roadmap for LSEG's MCP tools across various AI platforms, design product patterns for multi-step agentic workflows, and ensure the reliability and safety of autonomous AI agents interacting with LSEG financial data. You will collaborate with cross-functional teams and measure success through integration reach, workflow quality, and strategic impact.
- Définir la feuille de route d'intégration des outils MCP de LSEG à travers les plateformes d'IA, établir des modèles d'intégration et des architectures de référence.
- Définir les modèles de produit pour les flux de travail agentiques multi-étapes et multi-outils, concevoir des modèles de flux de travail et des mises en œuvre de référence.
- Concevoir des expériences d'intégration, des flux de travail d'exemple et des guides d'intégration qui permettent aux développeurs externes et aux partenaires de construire des applications agentiques.
- Experience in product management for integrations, APIs, developer platforms, or workflow/orchestration products
- Experience designing developer-facing products—SDKs, documentation, reference implementations, and sandbox environments
- Understanding of agentic AI patterns—tool chaining, multi-step reasoning, autonomous decision-making, and human-in-the-loop workflows
- Ability to work across ecosystem boundaries with external partners, developer communities, and platform providers
- Familiarity with AI/LLM ecosystems and agent frameworks (LangChain, CrewAI, AutoGen, Copilot Studio, or equivalent)
- Exposure to MCP, function-calling, or tool-use patterns in production LLM applications
- Background in financial services technology, capital markets workflows, or enterprise data integration
- Experience with partnership or ecosystem development in a platform or marketplace context
- Understanding of AI safety, guardrails, and governance considerations for autonomous agent systems
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