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LSEG

Global financial market infrastructure and data

Lead ML Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeLondon, UKNo salary listedIn-person

About the Job

Requirements

  • Strong Python development experience.
  • Hands-on experience with large language model and agent frameworks and agentic reasoning patterns.
  • Practical understanding of Model Context Protocol, including server and tool patterns.
  • Experience with FastAPI and REST API design and implementation.
  • Experience with prompt engineering and retrieval-augmented generation-based architectures.
  • Containerisation and Kubernetes-based deployment experience.
  • Ability to work across platform, product, and governance boundaries in an enterprise environment.

Responsibilities

  • Design and build MCP servers and tools that expose enterprise systems and workflows to AI agents.
  • Implement Skills that orchestrate tools, data, and reasoning into repeatable, governed workflows.
  • Contribute to the LSEG AI Assist agentic harness, including planning, tool-calling, and orchestration logic.
  • Build secure API wrappers where backend systems lack suitable authentication or entitlement models.
  • Work closely with product teams in a build-for capacity, transferring knowledge and establishing reusable patterns.
  • Shape the developer experience for MCP and Skills, including templates, contribution guidance, and standards.
  • Collaborate with Quality Engineers and Site Reliability Engineers to ensure solutions meet quality, governance, and operational readiness expectations.

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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