Snr Product Manager for MCP Integrations
London Stock Exchange Group
Stand out for this role — generate a tailored resume and cover letter in about a minute.
Benefits offered by this job
Job summary
London Stock Exchange Group (LSEG) is seeking a Senior Product Manager for MCP Integrations & Agentic Workflows to own the strategy, design and delivery of integration patterns and orchestration capabilities that connect LSEG MCP tools into multi-step, autonomous AI workflows.
You will shape how MCP tools are composed and orchestrated across partner ecosystems, third-party platforms, and internal agentic applications, enabling sophisticated financial workflows.
Qualifications
- Experience in product management for integrations, APIs, developer platforms.
- 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.
Responsibilities
- 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.
- 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.
- 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.
- 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 MCP capabilities within agent frameworks.
- Build and nurture a developer community around MCP integrations, gathering feedback and surfacing adoption blockers.
- Define guardrails, approval gates, and safety patterns for autonomous AI agents interacting with financial data.
Skills
Tools
Job description
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
LSEG is committed to offering competitive Compensation and Benefits. The anticipated base salary for this position is $78,900 - $131,500. Please be aware base salary ranges may vary by geographic location, city and state. In addition to our offered base salary, this role is eligible for our Annual Incentive Plan (AIP/”bonus plan”). Target AIP rates will be commensurate with role level and posted career stage. Individual salary will be reflective of job related knowledge, skills and equivalent experience.
LSEG roles (excluding internships and part‑time roles of less than 20 hours per week) are typically eligible for inclusion in our LSEG Benefits program, which includes offerings of: Annual Wellness Allowance, Paid time‑off, Medical, Dental, Vision, Flex Spending & Health Savings Options, Prescription Drug plan, 401(K) Savings Plan and Company match.
LSEG’s Benefits plan also includes basic life insurance, disability benefits, emergency backup dependent care, adoption assistance commuter assistance etc.
Join us and be part of a team that values innovation, quality, and continuous improvement. If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you. LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth. Our purpose is the foundation on which our culture is built.
Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions. Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.
We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives.
Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering. LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.
Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject.
If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.
'/%3e%3cpath%20d='M101.744%2012.4726L102.894%2016.1947L99.0021%2013.2201L101.744%2012.4726ZM105.3%208.40937H100.488L99.0026%203.59473L97.5116%208.41047L92.7%208.40385L96.5965%2011.3834L95.1055%2016.1942L99.0021%2013.2196L101.408%2011.3834L105.3%208.40992V8.40937Z'%20fill='white'/%3e%3cdefs%3e%3clinearGradient%20id='paint0_linear_5593_1381'%20x1='90'%20y1='9.44471'%20x2='99'%20y2='9.44471'%20gradientUnits='userSpaceOnUse'%3e%3cstop%20stop-color='%2300AD70'/%3e%3cstop%20offset='0.998594'%20stop-color='%2300B67A'/%3e%3cstop%20offset='1'%20stop-color='%23DCDCE6'/%3e%3c/linearGradient%3e%3c/defs%3e%3c/svg%3e){kind=small}
