Lead AI / ML Consultant

*Hi,* *Lead AI / ML Consultant* *FTE* *London, UK (Hybrid)* *Description:* We are seeking a highly experienced AI Consultant to design, implement, and drive enterprise-grade AI solutions on the Azure platform – Microsoft AI Foundry. This role combines hands-on experience, solution architecture, and technical leadership, with responsibility for guiding teams and proactively supporting multiple accounts and initiatives. The candidate needs to have deep insurance domain knowledge, a strong grip on modern AI architecture patterns, and the communication skills to operate comfortably in both technical and domain jargons. Key Responsibilities: * Deep understanding of the insurance domain: underwriting, policy administration, claims, reinsurance, and distribution. * Ability to speak credibly to business stakeholders about business impact without needing a translator * Familiarity with insurance data types: structured (policy, claims, exposure) and unstructured (loss reports, survey documents, correspondence). * Experience applying Responsible AI frameworks in practice: bias assessment, fairness metrics, explainability techniques and model cards. * Demonstrable hands-on experience with Microsoft Azure AI Foundry: project setup, model catalogue, evaluation frameworks, and deployment pipelines. * Proficiency with Azure OpenAI Service: GPT model deployment, fine-tuning, content filtering, and token management. * Experience with Azure AI Search (vector and hybrid search), Azure AI Document Intelligence, and Azure Machine Learning. * Ability to wire these services together into coherent, production-ready architectures — not just run individual demos. * Understanding of Azure security and identity controls as they apply to AI workloads: managed identities, private endpoints, and data residency. * Develop and deploy RAG-based knowledge systems using Azure AI Search, Azure OpenAI Service, and relevant orchestration frameworks (LangChain, Semantic Kernel, or Prompt Flow). * Design and implement AI agent architectures for orchestrating multi-step insurance workflows (e.g. automated claims triage, document extraction pipelines, underwriting assist tools). * Build and evaluate ML / predictive models relevant to insurance: churn, risk scoring, fraud detection, reserve estimation. * Validate outputs from engineering teams against the original solution design; identify deviations before they reach the client. * Establish and apply Responsible AI practices: bias evaluation, explainability, model monitoring, and governance documentation aligned to FCA and industry expectations. * Define reusable AI solution accelerators, reference architectures, and best-practice playbooks for the insurance vertical. * Ability to produce governance documentation that satisfies both technical and regulatory audiences. * Mentor and provide technical direction to junior consultants and engineers on the team. Required Skills \& Qualifications * Python proficiency sufficient to build prototypes, review engineering output, and debug issues independently. * Familiarity with orchestration frameworks: LangChain, Semantic Kernel, or Microsoft Prompt Flow. * Hands-on experience with Microsoft Azure AI Foundry * Working knowledge of Azure DevOps or GitHub for managing AI experiment tracking and deployment pipelines. * Ability to read and interpret SQL; experience with cloud data platforms (Databricks, Synapse, or equivalent) is advantageous. Preferred Qualifications/Certifications * Microsoft Certifications: AI-102 (Azure AI Engineer), DP-100 (Azure Data Scientist), AI-900, or equivalent. * Familiarity with insurance-specific AI regulation guidance. * Exposure to ML Ops practices: model versioning, drift detection, retraining pipelines, and A/B evaluation in production. * Experience with multi-modal AI (document + image pipelines relevant to property claims or risk surveys). * Familiarity with data bricks * Prior experience in a vendor or consultancy environment managing multiple concurrent client engagements. * Knowledge of CI/CD for Databricks (Azure DevOps, GitHub Actions). * Exposure to data governance, security, and compliance frameworks.