AI Architect – Data & Artificial Intelligence

We are seeking a highly experienced and visionary AI Architect to lead the design, governance, and delivery of enterprise-grade Data & Artificial Intelligence solutions within our insurance business. This is a senior technical leadership role that sits at the intersection of insurance domain knowledge, cloud-native data engineering, and cutting-edge Generative AI.

The successful candidate will serve as the primary technical authority for our AI strategy, shaping the architecture of platforms that underpin core insurance functions — including underwriting intelligence, claims automation, fraud detection, actuarial modelling, and customer experience personalisation. You will work closely with business leaders, product owners, data scientists, and engineering teams to translate complex insurance challenges into scalable, secure, and responsible AI solutions on Microsoft Azure.

Key Responsibilities

Architecture Strategy & Governance

• Define and own the enterprise Data & AI architecture strategy, roadmap, and reference architectures aligned to the organisation's insurance transformation agenda.

• Establish and enforce architecture standards, design principles, and governance frameworks across all data and AI initiatives.

• Lead architecture review boards, ensuring all AI solutions meet security, compliance, and Responsible AI standards — including regulatory requirements relevant to the insurance sector (e.g., Solvency II, GDPR, FCA/PRA guidelines).

• Develop and maintain a Responsible AI framework, embedding fairness, explainability, and auditability into model design — critical for insurance pricing, underwriting, and claims decisions.

• Champion data ethics and AI governance practices across the organisation, ensuring alignment with industry codes of conduct and emerging AI regulation.

Platform Design & Engineering

• Architect scalable, cloud-native data platforms on Microsoft Azure, leveraging Databricks, Azure Data Lake Gen2, Azure Synapse Analytics, Microsoft Fabric, and Azure Data Factory.

• Design and implement end-to-end Generative AI (GenAI) and Agentic AI solutions using Azure AI Foundry and Azure OpenAI, including Retrieval Augmented Generation (RAG), AI Agents, and Knowledge Retrieval pipelines.

• Define data mesh, data lakehouse, and federated data architectures to support insurance-specific data domains (policy, claims, customer, risk, actuarial).

• Oversee the design of real-time and batch data pipelines to support underwriting decisioning, claims triage, fraud analytics, and regulatory reporting.

• Establish vector database strategies and semantic search capabilities to power AI-driven knowledge management and customer-facing applications.

Insurance Domain AI Solutions

• Lead the architecture of AI-powered solutions for core insurance use cases: intelligent underwriting, automated claims processing, fraud detection & prevention, customer lifetime value modelling, and actuarial reserve estimation.

• Design AI agent workflows that integrate with core insurance systems (Policy Administration, Claims Management, CRM) via secure REST APIs and event-driven architectures.

• Partner with actuarial, underwriting, and claims teams to ensure AI models are fit-for-purpose, interpretable, and compliant with internal risk appetite frameworks.

• Provide architectural oversight for the deployment of predictive and prescriptive models into production insurance workflows.

Technical Leadership & Stakeholder Engagement

• Provide hands-on technical leadership and mentorship to Data Engineers, AI/ML Engineers, and Solution Architects across cross-functional squads.

• Collaborate with C-suite and senior business stakeholders to articulate AI strategy, communicate technical trade-offs, and build the business case for AI investment.

• Drive innovation through Proof-of-Concept (PoC) initiatives, technology evaluations, and horizon-scanning for emerging AI capabilities relevant to insurance.

• Lead solution design reviews, ensuring alignment with enterprise architecture, security standards, and total cost of ownership targets.

• Represent the organisation in external forums, vendor engagements, and industry working groups on AI and data innovation.

DevSecOps & Engineering Excellence

• Define and promote MLOps and DataOps practices, including CI/CD pipelines for model deployment, automated testing, and model monitoring in production.

• Establish Infrastructure as Code (IaC) standards for AI platform provisioning using Terraform or Bicep on Azure.

• Ensure all AI solutions are designed with security-by-default principles, including data encryption, access controls, network segmentation, and audit logging.

• Drive the adoption of reusable AI components, accelerators, and platform capabilities to reduce time-to-value across insurance business units.

Required Skills & Experience

Azure Data Platform (Mandatory)

• Azure Databricks (Delta Lake, Unity Catalog) – Expert

• Azure Data Factory (ADF) & Data Pipelines – Expert

• Azure Data Lake Storage Gen2 (ADLS) – Expert

• Azure Synapse Analytics – Proficient

• Microsoft Fabric (Lakehouse, Data Warehouse, Real-Time Intelligence) – Proficient

• PySpark, Python, SQL – Expert

AI & Generative AI (Mandatory)

• Azure AI Foundry (Mandatory) – Expert

• Azure OpenAI Service (GPT-4, embeddings, fine-tuning) – Expert

• Retrieval Augmented Generation (RAG) Architecture – Expert

• AI Agents & Agentic Workflow Design – Expert

• Prompt Engineering & LLM Evaluation – Proficient

• Vector Databases (Azure AI Search, Pinecone, Weaviate) – Proficient

• AI Governance, Responsible AI & Model Explainability – Expert

Engineering & DevOps

• Python (advanced) – Expert

• REST APIs & Microservices Architecture – Expert

• CI/CD – Azure DevOps / GitHub Actions – Proficient

• Infrastructure as Code (Terraform / Bicep) – Proficient

• MLOps / DataOps practices – Proficient

• Azure Kubernetes Service (AKS) / Containerisation – Desirable

Experience Requirements

• 8+ years of overall IT/technology experience, with a minimum of 4 years in Data Architecture at enterprise scale.

• 2+ years of hands-on experience designing and delivering production AI/GenAI solutions, including at least one Azure AI Foundry-based deployment.

• Demonstrable experience architecting enterprise-scale Azure Data Platforms in regulated industries, preferably insurance, banking, or financial services.

• Proven track record of leading AI architecture across the full lifecycle — from strategy and design through to production deployment and ongoing governance.

• Strong experience in stakeholder management at senior/executive level, with the ability to translate technical complexity into business value.

• Experience working within regulated environments, with a solid understanding of data privacy, model risk management, and AI compliance obligations.

Preferred Qualifications

• Insurance domain expertise: working knowledge of insurance products (P&C, Life, Health), core processes (underwriting, claims, actuarial), and regulatory frameworks (Solvency II, IFRS 17, FCA/PRA, Lloyd's of London standards).

• Exposure to AI orchestration frameworks:, LangGraph, Semantic Kernel, AutoGen, MCP (Model Context Protocol), or Copilot Studio.

• Experience with Databricks Mosaic AI for large-scale model training and serving.

• Familiarity with graph databases (e.g., Neo4j, Azure Cosmos DB for Gremlin) for fraud network analysis and relationship intelligence.

• Relevant certifications: Microsoft Azure Solutions Architect Expert, Azure AI Engineer Associate, Databricks Certified Data Engineer / ML Professional, or equivalent.

• Experience contributing to or leading AI Centre of Excellence (CoE) initiatives within a large enterprise.

Core Competencies

• Strategic Thinking: Ability to define long-term AI architecture vision and align it with business strategy and insurance transformation goals.

• Technical Leadership: Inspires and guides multi-disciplinary engineering teams; sets technical standards and fosters a culture of engineering excellence.

• Communication & Influence: Communicates complex AI concepts clearly to non-technical audiences; builds trust and credibility with senior stakeholders.

• Problem Solving: Approaches ambiguous, complex insurance challenges with structured thinking and creative, pragmatic solutions.

• Collaboration: Works effectively across business units, technology teams, vendors, and external partners in a matrixed organisation.

• Responsible Innovation: Balances the drive for AI innovation with a rigorous commitment to ethics, fairness, and regulatory compliance.

What We Offer

• A pivotal role in shaping the AI strategy of a leading insurance organisation undergoing significant digital transformation.

• Opportunity to work with cutting-edge AI technologies at enterprise scale, with access to the latest Azure AI capabilities.

• Collaborative, inclusive culture with a strong commitment to professional development and continuous learning.

• Competitive compensation package including base salary, performance bonus, and comprehensive benefits.

• Flexible and hybrid working arrangements.