AI Architect & .NET developer - EXL Service

Job Description: EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect.

We are headquartered in New York and have more than 60,000 employees spanning six continents. For more information, visit www.exlservice.com .

Role Title: AI Architect & .NET developer

BU/Segment: Analytics

Location: London, United Kingdom (Flexible hybrid working) OR Fully Remote within the United Kingdom

Employment Type: Permanent

Summary of the role:

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) 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

As part of your duties, you will be responsible for:

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
• OCR
• RAG systems

GenAI & Prompt Architecture

• Loss run and insurance document extraction & normalization
• Claims summarization, triage, and fraud signal generation
• Underwriting risk assessment and decision support

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

RAG & Knowledge Architecture

• Design RAG‑based knowledge architectures for policy, claims, and underwriting data
• Define chunking, embedding, retrieval, and grounding strategies

Enterprise & Platform Architecture - Azure

• Scalability and performance
• Cost optimization of LLM usage
• Security, data privacy, and access control