{"schemaVersion":"jobsearcher.job.v1","id":"b2f6ccbb50d5cf4c812e6e21","url":"https://jobsearcher.com/jobs/b2f6ccbb50d5cf4c812e6e21","canonicalUrl":"https://jobsearcher.com/jobs/b2f6ccbb50d5cf4c812e6e21","title":".Net GenAI Architect","description":"Job Title: AI Architect (Azure/.NET/React - GenAI & Agentic Systems)Location: RemoteWork Type: Contract/ Full TimeJob Description:As an AI Architect & .NET developer, you will be responsible for designing and governing end‑to‑end AI architectures on Azure ecosystem that enables intelligent automation and decision support across insurance functions such as underwriting, claims, reinsurance, and document‑heavy operations.The role focuses on building scalable, secure, and production‑grade GenAI platforms leveraging LLMs, Agentic AI, OCR to process complex unstructured insurance documents (e.g., loss runs, policy forms, claims reports, bordereaux) and generate accurate, explainable, and auditable outputs.You will define architectural patterns, lead the implementation team, and partner with business and technology stakeholders to ensure AI solutions are enterprise‑ready, cost‑efficient, and aligned with regulatory and operational constraints.Key ResponsibilitiesArchitecture & Solution DesignAct as an AI Architect and SME for GenAI‑driven insurance use casesDefine end‑to‑end AI architecture for unstructured document ingestion, reasoning, and output generationDesign LLM‑centric and hybrid AI architectures combining:OCRRAG systemsAgentic workflowsGenAI & Prompt ArchitectureDesign and govern prompt strategies and prompt frameworks for:Loss run and insurance document extraction & normalizationClaims summarization, triage, and fraud signal generationUnderwriting risk assessment and decision supportEstablish prompt versioning, testing, and optimization standards for enterprise useAgentic AI & Workflow OrchestrationArchitect Agentic AI systems for multi‑step reasoning, task decomposition, and tool orchestrationDefine patterns for human‑in‑the‑loop, approvals, and exception handlingDrive adoption of agent orchestration frameworks (LangGraph, AutoGen, CrewAI) in production scenariosRAG & Knowledge ArchitectureDesign RAG‑based knowledge architectures for policy, claims, and underwriting dataDefine chunking, embedding, retrieval, and grounding strategiesEnsure traceability and explainability of generated outputsEnterprise & Platform Architecture - AzureDrive architectural decisions related to:Scalability and performanceCost optimization of LLM usageSecurity, data privacy, and access controlAuditability and regulatory complianceDefine reference architectures and reusable components for multiple insurance use casesEvaluation, Quality & OptimizationEstablish evaluation frameworks for GenAI solutions, including:Precision, recall, and F1 metricsGrounding and hallucination detectionConsistency and explainability checksCollaboration & LeadershipPartner with business stakeholders (Underwriting, Claims, Actuarial, Legal) to shape AI roadmapsTechnical project lead experience 7Guide and mentor .net developers, react developers, and GenAI developersDefine best practices, standards, and architectural guardrails for GenAI adoptionTechnical Stack & Platform ExperienceProgramming & FrameworksStrong proficiency in .NET/ReactGenAI & LLM PlatformsAzure OpenAI APIs / enterprise LLM platformsArchitecture & IntegrationAPI‑first designMicroservices‑based architecturesExperience integrating AI solutions into enterprise systems","company":"Smart IT Frame","rawCompany":"smart it frame","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-08-14T14:34:25.233Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":".Net GenAI Architect","description":"Job Title: AI Architect (Azure/.NET/React - GenAI & Agentic Systems)Location: RemoteWork Type: Contract/ Full TimeJob Description:As an AI Architect & .NET developer, you will be responsible for designing and governing end‑to‑end AI architectures on Azure ecosystem that enables intelligent automation and decision support across insurance functions such as underwriting, claims, reinsurance, and document‑heavy operations.The role focuses on building scalable, secure, and production‑grade GenAI platforms leveraging LLMs, Agentic AI, OCR to process complex unstructured insurance documents (e.g., loss runs, policy forms, claims reports, bordereaux) and generate accurate, explainable, and auditable outputs.You will define architectural patterns, lead the implementation team, and partner with business and technology stakeholders to ensure AI solutions are enterprise‑ready, cost‑efficient, and aligned with regulatory and operational constraints.Key ResponsibilitiesArchitecture & Solution DesignAct as an AI Architect and SME for GenAI‑driven insurance use casesDefine end‑to‑end AI architecture for unstructured document ingestion, reasoning, and output generationDesign LLM‑centric and hybrid AI architectures combining:OCRRAG systemsAgentic workflowsGenAI & Prompt ArchitectureDesign and govern prompt strategies and prompt frameworks for:Loss run and insurance document extraction & normalizationClaims summarization, triage, and fraud signal generationUnderwriting risk assessment and decision supportEstablish prompt versioning, testing, and optimization standards for enterprise useAgentic AI & Workflow OrchestrationArchitect Agentic AI systems for multi‑step reasoning, task decomposition, and tool orchestrationDefine patterns for human‑in‑the‑loop, approvals, and exception handlingDrive adoption of agent orchestration frameworks (LangGraph, AutoGen, CrewAI) in production scenariosRAG & Knowledge ArchitectureDesign RAG‑based knowledge architectures for policy, claims, and underwriting dataDefine chunking, embedding, retrieval, and grounding strategiesEnsure traceability and explainability of generated outputsEnterprise & Platform Architecture - 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