Lead ML Engineer

Overview

In this role, you will design and build MCP-enabled servers and tools that expose enterprise systems to AI agents, and develop skills for orchestrating tools, data, and reasoning in governed workflows. You’ll contribute to the LSEG AI Assist harness, focusing on planning, tool-calling, and orchestration logic, while ensuring secure API wrappers and robust governance. You will collaborate with product, governance, and SRE teams to deliver scalable, maintainable AI capabilities. This is an opportunity to shape enterprise‑grade, self‑service AI platforms and patterns that scale across the organization.

Pay / Benefits

• healthcare
• retirement planning
• paid volunteering days
• wellbeing initiatives
• charitable foundation volunteering
• flexible working arrangements

Responsibilities

• Design and build MCP servers and tools exposing enterprise systems to AI agents
• Implement Skills to orchestrate tools, data, and reasoning into repeatable workflows
• Contribute to the LSEG AI Assist agentic harness (planning, tool-calling, orchestration)
• Build secure API wrappers for systems with weak authentication/entitlement
• Collaborate with product teams in a build-for mindset and promote reusable patterns
• Shape developer experience for MCP and Skills (templates, guidance, standards)
• Work with Quality Engineers and SREs to meet quality, governance, and operational readiness requirements

Key requirements

• Strong Python development experience
• Hands-on experience with LLM and agent frameworks
• Practical understanding of Model Context Protocol (MCP)
• FastAPI and REST API design/implementation
• Experience with prompt engineering and RAG-based architectures
• Containerisation and Kubernetes-based deployment experience
• Ability to operate across platform, product, governance boundaries in an enterprise

• cross-functional collaboration
• knowledge sharing
• governance and compliance awareness
• Python development
• LLM/agent frameworks
• MCP (Model Context Protocol)

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