Location
5 Canada Square, London

Hours
Full Time

Salary
Negotiable

About the Role
The Corporate Engineering AI (CE AI) team at London Stock Exchange Group (LSEG) is the central enablement and platform delivery function for LSEG’s internal agentic AI ecosystem. The team’s mission is to scale safe, high-quality AI capabilities across the enterprise by providing shared platforms, patterns, governance, and delivery support. CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway.

Rather than delivering individual business use cases end-to-end, the team enables product engineering groups across LSEG to expose knowledge, data, and actions to AI agents in a consistent, governed, and repeatable way. The team operates a Central MCP Delivery model: building critical MCP tools and services “for” product teams where required, while simultaneously defining standards, patterns, and platform capabilities that allow teams to progressively move towards self-service contribution.

The LSEG AI Assist / Internal MCP Programme delivers a production-grade agentic AI platform with MCP as its extensibility layer. This includes building and operating LSEG AI Assist, an in-house agentic experience capable of reasoning, planning, and tool-calling; operating QAS, the enterprise RAG and search layer used to ground agent responses in approved data sources; delivering a production Internal MCP Gateway providing discovery, security, policy enforcement, observability, and lifecycle management for MCP tools and Skills; designing and building MCP servers and Skills that expose internal and vendor systems safely to agents; and establishing evaluation, quality control, and governance mechanisms to promote MCP tools and Skills through PTB/PTO and operate them confidently at scale.

The programme emphasizes defining the future product and platform experience, patterns, and contribution pathways that will enable federated scale over time.

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

About you
You are a skilled ML engineer with a passion for building scalable, secure, and governed AI platforms. You thrive in collaborative environments and enjoy working closely with product teams to transfer knowledge and establish reusable patterns. You are committed to quality, governance, and operational readiness, and you bring a proactive approach to shaping developer experiences and standards.

Qualifications
Relevant advanced degree or equivalent experience in Machine Learning, Computer Science, or related fields is desirable. Proven track record in delivering production-grade AI/ML solutions in enterprise settings is highly valued.