AI Solutions Architect (Insurance & Azure AI)

Job Title: AI Solutions Architect (Insurance \& Azure AI) Job Location: London, United Kingdom (Hybrid) Job Type: FTE About the Opportunity We are looking for an experienced AI Solutions Architect to lead the design and delivery of enterprise-scale AI solutions within the Microsoft Azure ecosystem. This role combines technical leadership, solution architecture, client engagement, and hands-on implementation to deliver production-ready AI applications for the insurance sector. The successful candidate will possess extensive knowledge of insurance operations, modern AI technologies, cloud-native architectures, and the ability to communicate effectively with both technical teams and business stakeholders. What You'll Do AI Solution Architecture Design scalable AI and machine learning solutions using Microsoft's AI platform. Translate business requirements into production-ready AI architectures. Define technical approaches and oversee implementation across multiple client engagements. Ensure delivered solutions align with enterprise architecture and governance standards. Insurance Domain Expertise Work closely with stakeholders across underwriting, policy administration, claims processing, reinsurance, and insurance distribution. Understand insurance data models and operational workflows. Recommend AI-driven improvements for insurance business processes. Bridge communication between business users and engineering teams. Generative AI \& Intelligent Automation Develop Retrieval-Augmented Generation (RAG) solutions using Azure AI Search and Azure OpenAI. Build intelligent AI assistants and autonomous agents to streamline insurance workflows. Design document understanding solutions for claims, policy documentation, underwriting packs, and customer correspondence. Integrate multiple Azure AI services into cohesive enterprise applications. Azure AI Platform Deliver solutions using Microsoft Azure AI Foundry. Deploy and manage Large Language Models through Azure OpenAI Service. Implement semantic and vector search using Azure AI Search. Build document extraction pipelines with Azure AI Document Intelligence. Develop, deploy and monitor ML models using Azure Machine Learning. Responsible AI \& Governance Apply Responsible AI principles throughout the solution lifecycle. Perform model evaluation, explainability assessments, fairness reviews, and governance documentation. Support compliance with financial services regulatory expectations. Establish reusable governance templates and best practices. Technical Leadership Provide architectural guidance to engineering teams. Review technical deliverables and ensure adherence to solution designs. Mentor consultants and developers. Develop reusable frameworks, accelerators and reference implementations. Required Experience The ideal candidate should demonstrate experience in most of the following areas: Strong Python development skills. Enterprise solution architecture. Microsoft Azure AI Foundry. Azure OpenAI Service. Azure AI Search. Azure AI Document Intelligence. Azure Machine Learning. RAG application development. AI orchestration frameworks such as LangChain, Semantic Kernel or Microsoft Prompt Flow. Azure DevOps or GitHub-based CI/CD pipelines. SQL and relational databases. Experience working with cloud data platforms including Databricks, Azure Synapse or similar technologies. Deep understanding of insurance business processes. Excellent stakeholder communication skills. Nice to Have Candidates with experience in the following areas will be highly regarded: Microsoft certifications including AI-102, DP-100 or AI-900. MLOps practices including model versioning, automated deployment, monitoring and drift detection. Multimodal AI involving documents and images. Databricks development. Governance, security and compliance within regulated industries. Consultancy or client-facing delivery experience. CI/CD implementation for AI and data platforms. Experience delivering AI solutions within financial services or insurance organisations. Why Join? Work on enterprise AI transformation initiatives. Design innovative GenAI and intelligent automation solutions. Collaborate with cross-functional technical and business teams. Influence architecture standards and AI best practices. Mentor engineers and shape future AI capabilities.