Insurance AI Architect

Coforge; Dadri; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Coforge is hiring for an Insurance AI Architect in Greater Noida. You will architect AI-enabled underwriting and claims workflows across Duck Creek and Guidewire platforms, design REST/SOAP integrations, and guide MLOps, governance, and cloud-native AI deployments.

Ideal candidates have 12–18 years of experience in insurance tech, strong knowledge of ML/AI stacks, and hands-on experience with Duck Creek and Guidewire ecosystems. Location: Greater Noida, India.

Qualifications

• Working knowledge of Duck Creek OnDemand, Duck Creek Policy, Claims, Billing, and Rating modules.
• Familiarity with Guidewire InsuranceSuite architecture and data models.
• Experience with API-based integrations and middleware platforms.
• Knowledge of P&C commercial product structures and data models.

Tools

Duck Creek OnDemand

Duck Creek Policy

Duck Creek Claims

Duck Creek Billing

Duck Creek Rating

Duck Creek Data Insights

Duck Creek Author/Manuscript

Duck Creek low-code/no-code

Guidewire InsuranceSuite

PolicyCenter

ClaimCenter

BillingCenter

Gosu scripting

GW Cloud Platform

Integration Gateway

Cloud API

MuleSoft

Boomi

Azure Integration Services

LangChain

LlamaIndex

Semantic Kernel

CrewAI

Azure OpenAI

AWS Bedrock

Google Vertex AI

Anthropic Claude/API

XGBoost

LightGBM

Azure ML

SageMaker

Azure Form Recognizer

AWS Textract

MLflow

Copilot Studio

Microsoft Foundry

Kubernetes

Kafka

REST

SOAP

ACORD

ISO

Azure

AWS

GCP

Job description

Experience: 12-18 Years

Location: Greater Noida

We at Coforge are hiring for Insurance AI Architect

Insurance Industry & Platform Expertise

• Duck Creek Technologies: Working knowledge of Duck Creek OnDemand, Duck Creek Policy, Claims, Billing, and Rating modules; understanding of Duck Creek's Author/Manuscript configuration model, Duck Creek Data Insights, and Duck Creek's low-code/no-code extensibility framework
• Optional - Guidewire InsuranceSuite: Basic knowledge of PolicyCenter, ClaimCenter, and BillingCenter architecture, including Gosu scripting, PC/CC/BC data model, Integration Gateway, Cloud API, and Guidewire Cloud Platform (GWCP); familiarity with UI framework and Guidewire Marketplace apps
• Platform integration patterns: Experience with how AI services plug into both platforms via REST/SOAP APIs, event-driven architectures (Guidewire Cloud Events, Duck Creek's integration points), webhooks, and middleware (MuleSoft, Boomi, Azure Integration Services)
• Understanding of P&C Commercial & Specialty product structures: Rating algorithms, forms/endorsements, exposure bases, and how these map into platform data models

AI/ML Technical Stack

• LLM & GenAI frameworks: LangChain, LlamaIndex, Semantic Kernel; prompt engineering, RAG architecture design, and agentic frameworks ( CrewAI, or similar) for multi-step underwriting/claims workflows
• Foundation model platforms: Practical experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, and Anthropic Claude/API; model selection criteria (cost, latency, accuracy) for insurance-specific tasks
• Traditional ML/predictive modeling: Regression, gradient boosting (XGBoost/LightGBM) for risk scoring and pricing models; familiarity with actuarial modeling concepts as they intersect with ML
• Document AI/IDP: OCR and intelligent document processing (Azure Form Recognizer, AWS Textract) for submission intake, ACORD forms, loss runs, and SOV (statement of values) processing a common Commercial/Specialty use case
• MLOps & deployment: Model versioning, monitoring, and governance tooling (MLflow, Azure ML, SageMaker); CI/CD for AI pipelines integrated with platform release cycles
• Microsoft AI Platform Expertise: Copilot Studio, Foundry and Microsoft ecosystem integration
• Platform decision-making: Judgment on when to use Copilot Studio (low-code, business-user-facing agents) vs. AI Foundry (custom, code-first, higher-control agentic solutions) vs. open-source/other cloud AI stacks, based on client maturity, governance needs, and use case complexity
• Cloud platforms: Azure, AWS, or GCP; landing zone design, data lake/lakehouse architecture for insurance data
• Data engineering: ETL/ELT pipelines pulling from Duck Creek/Guidewire data models into analytics or AI-ready stores; understanding of insurance data standards (ACORD, ISO)
• API & microservices design: RESTful API design, event streaming (Kafka), and how to expose AI capabilities as composable services consumable by both platforms

Governance & Compliance

• Working knowledge of model risk management, explainability techniques
• Familiarity with SOC 2, data privacy (state insurance data regulations), and responsible AI frameworks as applied to carrier environments