Project Role Description

As an AI Architect & .NET developer, you will be responsible for designing and governing end-to-end AI architectures on the 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, and 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-effective, and aligned with regulatory and operational constraints.
Key Responsibilities
Architecture & Solution Design
- Act as an AI Architect and SME for GenAI-driven insurance use cases.
- Define end-to-end AI architecture for unstructured document ingestion, reasoning, and output generation.




- Design LLM-centric and hybrid AI architectures combining:
- OCR
- RAG systems
- Agentic workflows
GenAI & Prompt Architecture
- Design and govern prompt strategies and prompt frameworks for:
- Loss run and insurance document extraction & normalization
- Claims summarization, triage, and fraud signal generation
- Underwriting risk assessment and decision support
- Establish prompt versioning, testing, and optimization standards for enterprise use.
Agentic AI & Workflow Orchestration
- Architect Agentic AI systems for multi-step reasoning, task decomposition, and tool orchestration.
- Define patterns for human-in-the-loop, approvals, and exception handling.
- Drive adoption of agent orchestration frameworks (LangGraph, AutoGen, CrewAI) in production scenarios.
RAG & Knowledge Architecture
- Design RAG-based knowledge architectures for policy, claims, and underwriting data.
- Define chunking, embed

📌 AI Architect (India)
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📍 India