Description
The AI & Automation team at LSEG is transforming how the company operates through Artificial Intelligence, Automation, and Intelligent Engineering.
As a Core AI Engineer, you will play a leading technical role in designing, developing, and deploying AI solutions across the organisation.
Design & Build AI Solutions
- Design, develop, and deploy enterprise-grade AI products and services.
- Build agentic AI workflows, retrieval-augmented generation (RAG) 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.
Engineering Excellence
- 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 non-functional requirements including security, scalability, resilience, and observability.
Product & Platform Development
- 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 reliability and performance of deployed AI capabilities.
Innovation & Technical Leadership
- 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.
Business Impact
- 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.
Requirements
- 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.
Technical Skills
- Python and modern software engineering practices.
- Experience with Large Language Models (LLMs) and Generative AI.
- Agent frameworks and orchestration technologies.
- Retrieval Augmented Generation (RAG) architectures.
- API development and microservice design.
- Cloud-native development (Azure preferred).
- CI/CD automation and MLOps practices.
- Vector databases and knowledge retrieval platforms.
- Data modelling and distributed systems design.
- AI observability, evaluation, and governance frameworks.