Location
Paternoster Square, London

Hours
Full Time

Salary
Negotiable

About the Role
The AI & Automation team at London Stock Exchange Group (LSEG) is transforming how the organisation operates through Artificial Intelligence, Automation and Intelligent Engineering. We build enterprise-scale AI capabilities that improve service resilience, automate workflows, accelerate engineering productivity and enhance customer outcomes. As a Core AI Engineer, you will play a leading technical role in designing, developing and deploying AI solutions across the organisation. This hands-on engineering role combines software engineering, machine learning and AI platform expertise to turn innovative concepts into production-ready products delivering measurable business value. You will design and build scalable AI systems, solve complex technical challenges and influence enterprise AI adoption.

At LSEG, we are a global financial markets infrastructure and data business with a 300-year history of supporting financial stability and growth worldwide. Our culture embraces diversity, innovation and continuous learning, providing a rewarding environment where you can grow and fulfil your potential.

Experience
- Extensive software engineering experience delivering production-scale solutions
- Experience building AI or machine learning systems in enterprise environments
- Proven track record moving AI solutions from proof-of-concept to production
- Strong understanding of software architecture, engineering standards and operational practices
- Ability to influence technical direction across teams without formal management responsibility

Technical Skills
- Proficiency in Python and modern software engineering practices
- Experience with Large Language Models (LLMs) and Generative AI
- Knowledge of agent frameworks and orchestration technologies
- Familiarity with Retrieval Augmented Generation (RAG) architectures
- API development and microservice design expertise
- Cloud-native development experience (Azure preferred)
- CI/CD automation and MLOps practices
- Experience with vector databases and knowledge retrieval platforms
- Data modelling and distributed systems design
- AI observability, evaluation and governance frameworks

Desirable Experience
- 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

About You
- Deep technical curiosity and commitment to engineering excellence
- Strong ownership mindset and delivery focus
- Ability to solve ambiguous and highly complex problems
- Excellent stakeholder engagement and communication skills
- Collaborative leadership through influence
- Commitment to responsible and ethical AI development
- Passion for continuous learning and innovation

Qualifications
No specific formal qualifications are stated; however, extensive relevant experience and technical expertise are essential.