AI Consultant - Microsoft AI Foundry

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.