At a Glance
- Tasks: Lead the strategy and design of AI integration workflows for financial tools.
- Company: Join the London Stock Exchange Group, a leader in financial markets.
- Benefits: Competitive salary, wellness allowance, paid time off, and comprehensive health benefits.
- Other info: Collaborative culture with opportunities for personal growth and community involvement.
- Why this job: Shape the future of finance with cutting-edge AI technology and impactful projects.
- Qualifications: Experience in product management and understanding of AI integration patterns required.
The predicted salary is between 60000 - 100000 € per year.
As part of the LSEG AI team, we are hiring a Senior Product Manager - MCP Integrations & Agentic Workflows to own the strategy, design and delivery of integration patterns and agentic orchestration capabilities that connect LSEG's MCP tools into multi-step, autonomous AI workflows. This role is responsible for defining how LSEG's MCP tools are composed, chained, and orchestrated by AI agents across partner ecosystems (Claude, Copilot Studio, OpenAI, open-source frameworks), third-party platforms, and internal agentic applications. You will shape how LSEG's financial intelligence is consumed not just as individual tool calls, but as part of sophisticated, multi-step reasoning pipelines that automate real financial workflows. You will work at the frontier of agentic AI, defining how autonomous systems reliably interact with LSEG's data and analytics at enterprise scale.
Key Responsibilities & Accountabilities
- Integration Strategy & Ecosystem
- Define the integration roadmap for LSEG MCP tools across AI platforms including Anthropic (Claude), Microsoft (Copilot Studio, Azure AI), OpenAI, Google, and open-source agent frameworks (LangChain, CrewAI, AutoGen).
- Establish integration patterns, reference architectures, and best practices for connecting LSEG MCP tools to third-party agent orchestrators and workflow engines.
- Identify and prioritise strategic integration partnerships that expand the reach and utility of LSEG's MCP ecosystem.
- Agentic Workflow Design
- Define product patterns for multi-step, multi-tool agentic workflows - tool chaining, conditional branching, parallel execution, human-in-the-loop checkpoints, and error recovery.
- Design workflow templates and reference implementations for high-value financial use cases: morning briefings, equity research generation, portfolio rebalancing analysis, credit surveillance, and macro scenario modelling.
- Own the product requirements for orchestration reliability - ensuring agents handle tool failures, timeouts, ambiguous responses, and guardrail triggers gracefully.
- Developer & Partner Experience
- Design onboarding experiences, sample workflows, and integration guides that enable external developers and partners to build agentic applications on LSEG MCP tools.
- Define and maintain demo environments, sandbox configurations, and reference prompts that showcase LSEG's MCP capabilities within agent frameworks.
- Build and nurture a developer community around LSEG's MCP integrations, gathering feedback and surfacing adoption blockers.
- Reliability & Safety for Agentic Systems
- Define guardrails, approval gates, and safety patterns for autonomous AI agents interacting with LSEG financial data - ensuring agents cannot take unintended actions or surface misleading outputs.
- Partner with AI Governance and Model Risk to establish standards for agent auditability, decision traceability, and human oversight in agentic financial workflows.
- Design monitoring and alerting for agentic workflow health - tracking completion rates, failure modes, tool call patterns, and cost efficiency across agent-driven pipelines.
- Cross-Functional Collaboration
- Work closely with the Financial Domain Tools PM to ensure tools are designed for composability and chaining within agent workflows.
- Partner with the MCP Platform PM to ensure the infrastructure supports orchestration patterns - session continuity, context passing, and multi-tool transactions.
- Collaborate with commercial and business development teams to position LSEG's agentic MCP capabilities with strategic partners and enterprise clients.
- Engage with LSEG product teams across divisions to identify and instrument high-value agentic use cases.
Skills & Competencies
Required
- Experience in product management for integrations, APIs, developer platforms, or workflow/orchestration products.
- Understanding of agentic AI patterns - tool chaining, multi-step reasoning, autonomous decision-making, and human-in-the-loop workflows.
- Familiarity with AI/LLM ecosystems and agent frameworks (LangChain, CrewAI, AutoGen, Copilot Studio, or equivalent).
- Experience designing developer-facing products - SDKs, documentation, reference implementations, and sandbox environments.
- Ability to work across ecosystem boundaries with external partners, developer communities, and platform providers.
Preferred
- 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.
Measures of Success
- Integration Reach & Adoption
- Number of AI platforms and agent frameworks with active, supported LSEG MCP integrations.
- Growth in agentic workflow invocations across partner ecosystems.
- Developer adoption metrics - onboarding completions, active integrations, community engagement.
- Workflow Quality & Reliability
- Agentic workflow completion rates, failure rates, and mean-time-to-recovery across supported patterns.
- Reduction in agent-driven errors, hallucination-related tool misuse, and unintended data exposure incidents.
- Quality and coverage of workflow templates and reference implementations for key financial use cases.
- Strategic Impact
- Number of strategic partner integrations (AI platforms, fintechs, enterprise clients) enabled through MCP.
- Contribution to new commercial revenue streams driven by agentic MCP capabilities (partnerships, Model-as-a-Service, API consumption).
- Influence on LSEG's positioning as the leading financial data provider for AI agent ecosystems.
Snr Product Manager for MCP Integrations - London Stock Exchange Group employer: London Stock Exchange Group
At London Stock Exchange Group, we pride ourselves on fostering a dynamic and inclusive work environment that champions innovation and personal growth. As a Senior Product Manager for MCP Integrations, you will be at the forefront of cutting-edge AI technology, with access to comprehensive benefits including competitive salaries, wellness allowances, and opportunities for professional development. Join us in our mission to drive financial stability and empower economies while enjoying a collaborative culture that values your individuality and contributions.
Contact Detail:
London Stock Exchange Group Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Snr Product Manager for MCP Integrations - London Stock Exchange Group
✨Tip Number 1
Network like a pro! Reach out to folks in your industry, especially those at LSEG or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Prepare for interviews by diving deep into LSEG's products and services. Show us you know your stuff and how your experience aligns with the role. Bring examples of how you've tackled similar challenges in the past.
✨Tip Number 3
Don’t just wait for job postings! Keep an eye on our website and apply directly. Sometimes, the best opportunities come from being proactive and showing your interest before a role is even advertised.
✨Tip Number 4
Follow up after interviews! A quick thank-you note can leave a lasting impression. It shows you're genuinely interested and keeps you on our radar as we make decisions.
We think you need these skills to ace Snr Product Manager for MCP Integrations - London Stock Exchange Group
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Senior Product Manager role. Highlight your experience with integrations, APIs, and AI workflows, as these are key to what we're looking for at LSEG.
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work that relate to agentic AI patterns and product management. We want to see how you’ve tackled challenges similar to those we face.
Be Clear and Concise:Keep your application straightforward and to the point. Use clear language and avoid jargon unless it’s relevant. We appreciate clarity, especially when discussing complex topics like financial workflows.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows your enthusiasm for joining our team at LSEG!
How to prepare for a job interview at London Stock Exchange Group
✨Know Your Integration Strategies
Before the interview, dive deep into LSEG's MCP tools and their integration with AI platforms. Familiarise yourself with the integration roadmap and be ready to discuss how you would define and implement effective integration patterns.
✨Showcase Your Workflow Design Skills
Prepare examples of multi-step workflows you've designed in the past. Be ready to explain your approach to tool chaining, conditional branching, and error recovery, as these are crucial for the role.
✨Understand the Developer Experience
Think about how you can enhance the onboarding experience for developers using LSEG's MCP tools. Bring ideas on creating sample workflows and integration guides that could help external developers build agentic applications.
✨Emphasise Safety and Reliability
Be prepared to discuss how you would ensure the reliability and safety of autonomous AI agents interacting with financial data. Highlight your understanding of guardrails and approval gates, and how they can prevent unintended actions.
