Core AI Engineer
Posted Updated
- The AI & Automation team is transforming how LSEG operates through the use of Artificial Intelligence, Automation and Intelligent Engineering. We are building enterprise-scale AI capabilities that improve service resilience, automate operational workflows, accelerate engineering productivity and enhance customer outcomes
- As a Core AI Engineer, you will play a leading technical role in the design, development and deployment of AI solutions across the organisation. You will combine software engineering, machine learning and AI platform expertise to turn innovative concepts into production-ready products that deliver measurable business value
- 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
- 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
- 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
- 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. The Lead/IC profile is expected to guide technical outcomes and raise capability through collaboration while remaining deeply hands-on
- 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
- 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