Job Title

Key ResponsibilitiesAs a Generative AI Architect, you will: Design and Implement Intelligent Agents: Lead the architecture, development, and deployment of sophisticated multi-step intelligent agents using LangGraph for complex workflows. Integrate and Optimize AI Tools: Leverage MCP tools effectively within agent designs to enhance functionality and performance. Cloud-Native Deployment: Implement and manage agent deployments on Azure AI Foundry and Functions , ensuring scalable, robust, and efficient operations. RAG Stack Optimization: Work with the broader retrieval-augmented generation (RAG) stack, including embeddings, vector databases, and chunking strategies , to enable intelligent document understanding across insurance submissions and claims. Agent Orchestration & Debugging: Comfortably engineer prompts, orchestrate agent interactions, and meticulously debug complex multi-step agent behaviors. Develop Specific Agent Use Cases: Submissions Agent: Build agents to parse submission emails and documents, extract critical data, apply underwriting processing and knowledge, and prioritize tasks with full transparency and repeatability. Bordereaux Reconciliation Agent: Automate the matching of premium and policy data across bordereaux files and internal systems. Claims Notification Agent: Develop agents to ingest claim notices and surface critical items requiring human intervention. Supervisor Agent: Design and implement a supervisor agent to coordinate graph-based task execution and ensure secure data handling per client. Bordereaux Extraction Agent: Work with unstructured data, vision processing, and LLMs for accurate data extraction. Required Skills & ExperienceExpertise in LLM Frameworks: Strong hands-on experience with LangChain, LangGraph, and LangSmith . Cloud AI Platforms: Familiarity with Azure AI Foundry and Functions and best practices for cloud-native deployment patterns. RAG Fundamentals: Deep understanding of RAG architectures, embeddings, and vector stores . Prompt Engineering: Proven ability in prompt engineering, agent orchestration, and effective debugging of AI workflows. Architecture Acumen: Familiarity with MCP Tools and architecture . Bonus QualificationsEnterprise LLM Applications: Demonstrated experience building and deploying enterprise-grade LLM applications .