Greater Noida Uttar Pradesh Architect Jobs – 150 Open Jobs Today

Insurance AI Architect
Coforge Ltd. —Greater Noida, Uttar Pradesh
- Azure
- Master's degree
- AWS
2h
Architect
Antara Senior Living —Noida, Uttar Pradesh
- Bachelor's degree
Architect - Application Development Microsoft N 4D
Genpact India Pvt. Ltd. —Noida, Uttar Pradesh
- Full-time
- Hybrid work
- Azure
- Oracle
- Computer Science
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Interior Designer
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Understand client requirements and translate them into functional design solutions. Basic knowledge of interior design software. Fresher to 3 years experience.
₹18,000 - ₹35,000 a month
Quick apply
Senior Interior Designer
Archohm Consults —Noida, Uttar Pradesh
We are seeking an experienced and talented Interior Designer to lead our interior design team in creating stunning and functional spaces that exceed client…
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Insurance AI Architect

Coforge Ltd. -
Greater Noida, Uttar Pradesh

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Job details

2 hours ago

Qualifications

CI/CD
Pricing
Azure
Cloud architecture
Law
Master's degree
SOAP
OS Kernels
AWS
Machine learning
Continuous integration
REST
APIs
UI
Kafka
AI
Billing
Analytics

Full job description

Job Description
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 ofPC 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

Data Cloud Architecture

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 ofmodel risk management, explainability techniques
Familiarity withSOC 2, data privacy (state insurance data regulations), and responsible AI frameworks as applied to carrier environments

Executive Stakeholder Communication

CXO-level engagement
Executive storytelling influence
Trusted advisor positioning
Change management fluency

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