AI Solution Architect (Insurance) - Agentic AI & Azure

Agentic AI Architecture Design end‑to‑end agentic solutions on Azure, from interaction to orchestration to observability. Define multi‑agent patterns that collaborate across underwriting, claims, and servicing. Apply Azure OpenAI, prompt orchestration, tool/skills calling, memory, and planning patterns. Establish autonomy guardrails, human‑in‑the‑loop checkpoints, and decision traceability. Build LLM‑driven reasoning + retrieval for document‑intensive flows (FNOL, submissions, endorsements, SIU, etc.). Deliver conversational and task agents that integrate with core insurance platforms and data. Design secure integrations with policy admin, claims, billing, CRM, and document management systems. Implement RAG patterns using Azure data and search services with content safety and observability. Architect to insurance regulatory requirements (privacy, retention, auditability). Implement prompt safety, content filtering, audit logging, and explainability. Enforce identity, access, and data protection with Azure‑native security services. Provide architectural oversight across delivery teams; run design reviews and client workshops. Lead pre‑sales solutioning, reference architectures, demos, and technical storytelling. 7+ years in solution architecture or enterprise technology roles (e.g., architect, principal engineer, platform lead). 3+ years delivering solutions for the insurance domain (P&C, Life, Health, or Reinsurance) in a carrier, MGA/MGU, broker, or consulting context. 2+ years architecting or building LLM/GenAI applications in production or regulated enterprise settings. 2+ end‑to‑end Azure‑hosted AI solutions delivered (from design to deployment) with measurable adoption. Bachelor's degree in Computer Science, Engineering, Data/AI, or related field. Ability to travel 30%. Experience with multi‑agent frameworks or orchestration layers (e.g., Semantic Kernel, LangChain, Autogen, custom planners). Exposure to Copilot‑style architectures and enterprise conversational AI (e.g., role grounding, tool/plugin ecosystems). Azure certifications (e.g., AZ‑305 Azure Solutions Architect Expert, AI‑102 Azure AI Engineer Associate). Consulting background with client‑facing architecture leadership (pre‑sales, roadmaps, value cases).