Core AI Engineer
London Stock Exchange Group2 hours ago
London, United KingdomStaff+
Responsibilities
- Design, develop, and deploy enterprise-grade AI products and services.
- Build agentic AI workflows, RAG solutions, LLM integrations, MCP service integrations, vector database solutions, and intelligent automation capabilities.
- Develop reusable AI frameworks, accelerators, engineering standards, APIs, orchestration services, and automation pipelines.
- Define solution architecture and engineering patterns for AI products and drive security, scalability, resilience, and observability requirements.
- Partner with Product Managers, Data Scientists, Engineering, Operations, and Product teams to deliver AI solutions from concept through production.
- Develop AI platforms, monitoring, evaluation, and governance processes that enable broader engineering adoption.
- Improve the reliability and performance of deployed AI capabilities.
- Provide technical direction, mentor engineers, evaluate emerging AI technologies, and influence architecture and engineering practices.
- Translate business challenges into scalable AI solutions, define KPIs, and deliver productivity, resilience, and customer-value improvements.
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.
- Proficiency in Python and modern software engineering practices.
- Experience with LLMs, Generative AI, agent frameworks, orchestration technologies, RAG architectures, API development, microservice design, vector databases, knowledge retrieval platforms, data modelling, distributed systems, AI observability, evaluation, and governance frameworks.
- Experience with cloud-native development, with Azure preferred, CI/CD automation, and MLOps practices.
- Ability to influence technical direction across teams without formal management responsibility.
- Experience in financial services or highly regulated environments is desirable.
- Knowledge of SRE principles, AI-powered operational tooling, internal AI platforms, developer enablement capabilities, Microsoft AI ecosystem, Copilot technologies, and Azure AI services is desirable.
- Strong technical curiosity, ownership, delivery focus, problem-solving ability, stakeholder engagement, communication, collaborative leadership, and commitment to responsible AI development.
Benefits
- Healthcare benefits, retirement planning, paid volunteering days, and wellbeing initiatives.
- Collaborative and creative culture with opportunities for innovation, continuous learning, and professional growth.
- Equal-opportunity workplace with reasonable accommodation for religious practices, mental health needs, and physical disabilities.
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