AI LLM Technology Architecture

In this role you design and deliver customer-focused AI solutions, spanning genAI, ML and analytics, to enable growth, better personalization and efficient service. You work with cross-functional teams to shape target architecture, own workstreams, and guide engineers from design to production. You’ll translate technical concepts into business terms and help customers realise measurable value. The opportunity centers on applying AI to client growth, marketing, commerce and service challenges at scale.

• Competitive base salary
• Annual performance bonus
• Opportunity for equity
• 25 days leave plus 3 volunteering days
• Family-friendly and flexible policies
• Pension plan with financial wellbeing support

• Design architectures for AI, GenAI and analytics across the customer lifecycle (marketing, commerce, product, sales, service)
• Own defined components or workstreams within the technical architecture ensuring scalability, security and business alignment
• Build AI applications and platform components, integrating ML, GenAI and agentic AI with enterprise systems (CRM, CDP, CMS, DAM, cloud data platforms)
• Influence architectural decisions on technology selection, integration patterns, build-versus-buy, security, governance and operations
• Provide technical direction to small delivery teams from concept to production deployment and optimization
• Design responsible AI solutions with security, privacy, and regulatory controls and monitoring
• Share best practices, mentor junior engineers/data scientists and raise standards across the Craft
• Support business development with solution approaches, estimates and technical roadmaps for AI opportunities
• Build strong relationships with client stakeholders and explain technical concepts to diverse audiences

• Production GenAI experience
• Customer-domain AI experience (growth, personalization, marketing, commerce, sales, or service)
• Modern AI architecture knowledge (LLMs, RAG, agentic systems)
• Engineering and cloud foundations with hands-on delivery (Azure, AWS or GCP)
• Enterprise data integration, governance, security and quality considerations
• Technical leadership within delivery teams and ownership of design decisions
• Consulting and stakeholder management skills
• Responsible AI, governance and security experience
• Mentoring and knowledge sharing within teams

• Collaborative working style
• Clear communication with technical and non-technical stakeholders
• Mentoring and coaching
• GenAI/LLM production experience
• RAG (retrieval-augmented generation)
• Agentic AI capabilities