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Location
In office (London)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Aug 23, 2026. London Stock Exchange scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Headquartered in London, United Kingdom, the London Stock Exchange is one of the world's oldest and most prominent financial exchanges. It provides international capital markets, premier listing venues such as the Main Market and AIM, and electronic trading infrastructure for equities, bonds, and exchange-traded funds. As a core subsidiary of the London Stock Exchange Group, it connects global issuers with investors to facilitate efficient capital formation, market liquidity, and economic growth.

Join LSEG's AI & Automation team as a Core AI Engineer, where you will play a leading technical role in the design, development, and deployment of AI solutions across the organization. You will combine software engineering, machine learning, and AI platform expertise to turn innovative concepts into production-ready products that deliver measurable business value. This is a hands-on engineering role for someone passionate about building scalable AI systems and solving complex technical challenges.

Missions

  • Design, develop, and deploy enterprise-grade AI products and services, including agentic AI workflows and intelligent automation capabilities.
  • Lead technical implementation across multiple AI initiatives, defining solution architecture and engineering patterns for AI products.
  • Act as a technical leader across AI initiatives, mentoring engineers and contributing to the development of AI engineering capability.

Profil recherché

- This is a hands-on engineering role for someone passionate about building scalable AI systems, solving complex technical challenges and influencing the direction of enterprise AI adoption

- Demonstrated experience moving AI solutions from proof-of-concept into production

- Strong understanding of software architecture, engineering standards and operational practices

- Extensive software engineering experience delivering production-scale solutions

- Ability to influence technical direction across teams without formal management responsibility

- Experience building AI or machine learning systems in enterprise environments

- Cloud-native development (Azure preferred)

- Retrieval Augmented Generation (RAG) architectures

- AI observability, evaluation and governance frameworks

- API development and microservice design

- CI/CD automation and MLOps practices

- Python and modern software engineering practices

- Data modelling and distributed systems design

- Agent frameworks and orchestration technologies

- Vector databases and knowledge retrieval platforms

- Experience with Large Language Models (LLMs) and Generative AI

- Experience within Financial Services or highly regulated environments

- Knowledge of Service Reliability Engineering (SRE) principles

- Experience developing AI-powered operational tooling

- Experience building internal AI platforms or developer enablement capabilities

- Familiarity with Microsoft AI ecosystem, Copilot technologies and Azure AI services

- Collaborative leadership through influence

- Strong ownership mindset and delivery focus

- Commitment to responsible and ethical AI development

- Deep technical curiosity and engineering excellence

- Ability to solve ambiguous and highly complex problems

- Passion for continuous learning and innovation

- Excellent stakeholder engagement and communication skills

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