We have a great new role for an Enterprise Architect - AI & Automation to join our Technology Transformation team.
As Enterprise Architect – AI & Automation, you will shape and drive the enterprise architecture for AI-enabled platforms, data products and hyper-automation across the CTO estate.
You will work across CTO verticals to embed architectural patterns that enable AI at scale, closed-loop automation, and measurable cost and efficiency benefits, while ensuring solutions remain secure, governed and cloud-agnostic by design.
This is a hands-on, highly influential role requiring deep technical credibility, strong stakeholder engagement, and the ability to translate ambition into executable architecture.
This role would be well suited for an existing AI/Automation Architect or Tech Lead, Senior Developer, Senior Devops Engineer with extensive AI/Automation.
Key responsibilities and accountabilities Define and own enterprise-level AI and automation architecture patterns, reference designs and guardrails.
Shape the evolution of the AI factory (data → model → inference → action), leveraging GCP capabilities while avoiding provider lock-in.
Establish standards for ML Ops, model lifecycle management, data governance, observability and ethical AI.
Embed within CTO verticals to guide initiatives from early discovery through to delivery and operationalisation.
Partner with Solution Architects, Tech Leads and engineering squads to ensure architectural intent is realised.
Drive reuse of common AI, data and automation capabilities to reduce duplication, cost and time to value.
Identify opportunities where AI and automation can drive cost reduction, operational efficiency and resilience.
Architect closed-loop automation patterns spanning intent ingestion, decisioning, orchestration and assurance.
Qualifications Proven experience as an AI/Automation Architect or Tech Lead, Senior Developer, Senior Devops Engineer with extensive AI, data and automation experience .
Strong hands‑on understanding of AI/ML architectures, MLOps, data pipelines and event‑driven systems.
Proven hands‑on experience with key AI technologies and concepts such as LLMs, Scikit, prompt engineering, LangChain, vector databases, graph databases, Lucene, Lakehouse and retrieval‑augmented generation (RAG).
Hands on production experience deploying and monitoring AI/ML systems on cloud platforms such as AWS, GCP or Azure.
Knowledge of modern data architectures (data products, data contracts, governance, lineage, quality).
Experience with automation, decisioning engines, workflow orchestration and closed‑loop control.
Strong understanding of agentic AI concepts, including: tool‑using agents, planning and reasoning loops, multi‑agent coordination, memory, context and state management.
Experience designing AI systems that combine LLMs/SLMs with deterministic components such as rules engines, policies, workflows and orchestration.
Excellent communication, influencing and stakeholder management skills.
Equal opportunities employer. We are working hard to remove bias and barriers for our people and candidates. We support and encourage you to be your authentic self throughout your application journey with us.
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