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.

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