ai engineer in financial markets infrastructure

LSEG is a global financial markets infrastructure and data provider. It enables businesses and economies to fund innovation, manage risk and create jobs through trusted financial market infrastructure services and an open-access model.

• Design, develop and deploy enterprise-grade AI products and services;
• Build agentic AI workflows, retrieval-augmented generation solutions and intelligent automation capabilities;
• Deliver scalable integrations with LLMs, MCP services, vector databases and enterprise platforms;
• Develop reusable AI frameworks, accelerators and engineering standards;
• Lead technical implementation across multiple AI initiatives;
• Define solution architecture and engineering patterns for AI products;
• Build robust APIs, orchestration services and automation pipelines;
• Drive security, scalability, resilience and observability requirements;
• Partner with Product Managers, Data Scientists and Engineering teams to deliver AI solutions from concept through production;
• Support the development of AI platforms that enable wider engineering adoption;
• Establish monitoring, evaluation and governance processes for AI systems;
• Improve the reliability and performance of deployed AI capabilities;
• Act as a technical leader across AI initiatives;
• Mentor engineers and contribute to the development of AI engineering capability;
• Evaluate emerging AI technologies and identify opportunities to accelerate delivery;
• Provide technical direction on architecture, tooling and engineering practices;
• Translate business challenges into scalable AI solutions;
• Define measurable KPIs and success measures;
• Ensure solutions drive productivity improvements, operational resilience and customer value;
• Partner with stakeholders across Engineering, Operations and Product organisations.

• Extensive software engineering experience delivering production-scale solutions;
• Experience building AI or machine learning systems in enterprise environments;
• Demonstrated experience moving AI solutions from proof of concept into production;
• Strong understanding of software architecture, engineering standards and operational practices;
• Ability to influence technical direction across teams without formal management responsibility;
• 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;
• Nice to have: Experience within Financial Services or highly regulated environments, knowledge of Service Reliability Engineering 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.

London, England, United Kingdom; Healthcare, retirement planning, paid volunteering days and wellbeing initiatives.