Role Description We're seeking an experienced AI/ML Architect with a strong Data Science background to design and deliver enterprise-scale AI and machine learning solutions. You'll work across advanced AI initiatives, helping shape scalable, production-ready solutions that support: - Optimisation models - Intelligent edge capabilities - Emerging Agentic AI technologies Qualifications - Extensive experience in AI, Machine Learning, Data Science, or Solution Architecture - Strong experience designing and deploying production AI/ML solutions - Hands-on experience with Azure Machine Learning, Azure AI Foundry, and the Microsoft AI ecosystem - Experience working with Large Language Models (LLMs) and Agentic AI frameworks - Knowledge of Microsoft Agent Framework - Experience with Azure Kubernetes Service (AKS) - Familiarity with Redis and Azure Cosmos DB for AI memory architectures is highly desirable - Excellent communication skills with the ability to engage both technical and business stakeholders Requirements - Software engineering or application development background preferred - Experience with optimisation models, predictive analytics, or computer vision is advantageous Benefits - Quality, accountability, and honesty in our work - A healthy, supportive team environment - Integrity in our commitments - Opportunities for professional growth and expertise in data and AI - Focus on building trusted partnerships - Encouragement of diversity and individuality within the team

• Create and review finance-related prompts, scenarios, and analytical tasks. • Evaluate AI-generated responses for financial accuracy, reasoning quality, and business relevance. • Apply subject matter expertise to improve model performance and financial understanding. • Review financial analyses, assumptions, calculations, and recommendations. • Identify inaccuracies, inconsistencies, and areas for improvement. • Provide structured feedback and quality assessments. • Collaborate with project teams to maintain high-quality deliverables. • Meet established project timelines and productivity goals.

• Create and review finance-related prompts, scenarios, and analytical tasks. • Evaluate AI-generated responses for financial accuracy, reasoning quality, and business relevance. • Apply subject matter expertise to improve model performance and financial understanding. • Review financial analyses, assumptions, calculations, and recommendations. • Identify inaccuracies, inconsistencies, and areas for improvement. • Provide structured feedback and quality assessments. • Collaborate with project teams to maintain high-quality deliverables. • Meet established project timelines and productivity goals.

• Create and review finance-related prompts, scenarios, and analytical tasks. • Evaluate AI-generated responses for financial accuracy, reasoning quality, and business relevance. • Apply subject matter expertise to improve model performance and financial understanding. • Review financial analyses, assumptions, calculations, and recommendations. • Identify inaccuracies, inconsistencies, and areas for improvement. • Provide structured feedback and quality assessments. • Collaborate with project teams to maintain high-quality deliverables. • Meet established project timelines and productivity goals.