Lead Insurance Domain Architect

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The Lead Insurance Domain Architect is a senior, client-facing domain leadership role responsible for translating insurance business needs into clear, actionable solution requirements and ensuring that technology solutions remain aligned with insurance processes, products, regulations, and business outcomes.

The role acts as the primary bridge between Insurance Domain stakeholders, Product Owners, Technology Architecture, AI/Data Science, Engineering, and Validation teams. The Domain Architect plays a central role in converting prototypes and business concepts into specifications, supporting backlog refinement, guiding builders, and ensuring that delivered solutions are validated against business intent.

The ideal candidate combines deep insurance industry expertise with strong solution-shaping capabilities and an understanding of AI-led, specification-driven development, where AI-assisted engineering tools accelerate the journey from business intent and specifications through implementation and validation.

Key Responsibilities:

Insurance Domain Architecture & Solution Shaping

• Serve as the domain authority for insurance business capabilities, processes, products, data, and operating models.
• Translate business objectives and insurance use cases into domain architecture, business specifications, functional requirements, and acceptance criteria .
• Define the business context and domain boundaries required for technology and AI-enabled solutions.
• Ensure proposed solutions align with insurance industry practices, regulatory requirements, enterprise standards, and target business outcomes.
• Identify dependencies and impacts across the insurance value chain, including upstream and downstream processes and systems.

AI-Led, Specification-Driven Development

• Understand and actively participate in an AI-led, specification-driven development process , where well-defined specifications become the foundation for AI-assisted solution development.
• Translate business intent into precise, structured, and implementation-ready specifications that can be effectively consumed by both engineering teams and AI-assisted development tools.
• Work iteratively with Product Owners, Architects, and Builders to refine specifications based on generated solutions, prototypes, test results, and business feedback.
• Understand how AI coding assistants and agentic development tools can accelerate prototyping, code generation, testing, documentation, and solution refinement.
• Be familiar with modern AI-assisted development environments and tools such as GitHub-based development workspaces/tools, GitHub Copilot, Claude Code, or comparable AI coding and agentic engineering tools .
• Help establish effective feedback loops across business intent → specification → AI-assisted build → test → domain validation → specification refinement .
• Ensure that AI-generated implementations remain traceable to approved business requirements and insurance-domain rules.
• Apply appropriate judgment and governance when reviewing AI-generated specifications, code, test scenarios, and solution behavior.

Prototype & Business Concept Elaboration

• Partner closely with the Lead Domain Advisory and Prototyper roles to convert business concepts into viable solution prototypes.
• Evaluate prototypes from an insurance-domain perspective and determine whether they accurately represent business workflows and user needs.
• Refine prototype outputs into requirements and specifications that can be industrialized by engineering teams.
• Facilitate rapid feedback between business stakeholders and technical teams during prototype iterations.
• Ensure successful prototypes have a clear path from experimentation to production implementation.

Specifications & Backlog Definition

• Convert insurance business requirements and prototype outcomes into clear functional specifications, user stories, business rules, workflows, and acceptance criteria .
• Develop specifications with sufficient precision and structure to support both traditional engineering and AI-assisted implementation .
• Collaborate with Product Owners to establish and refine the solution backlog.
• Support prioritization based on business value, risk, dependencies, regulatory requirements, and implementation complexity.
• Resolve domain questions and ambiguities that arise during development.
• Maintain traceability from business objectives through specifications, implementation, testing, and validation.

Collaboration with Engineering & Builder Teams

• Work closely with Builders/Engineering teams throughout implementation.
• Provide insurance-domain guidance during solution development and clarify specifications as required.
• Participate in AI-assisted development workflows where specifications and domain models are used to accelerate implementation.
• Review generated or implemented solutions to ensure they preserve intended insurance business behavior.
• Participate in design reviews, sprint refinement, demonstrations, and solution walkthroughs.
• Collaborate with Product Owners and Builders to identify gaps early and minimize downstream rework.

Partnership with Technology Architecture

• Collaborate with the Technology Architect to ensure business and technology architectures are aligned.
• Provide domain requirements and constraints needed to develop the overall Solution Blueprint .
• Contribute insurance business architecture, process flows, capability models, business rules, and domain data requirements.
• Evaluate technology architecture decisions for their impact on insurance operations, customer experience, regulatory obligations, and business scalability.
• Help ensure reusable platforms and components appropriately support insurance-specific capabilities.

AI & Data Collaboration

• Partner with AI/Data Scientists and Technology Architects to define insurance data and AI requirements.
• Identify relevant insurance data entities, business terminology, relationships, rules, and semantic context required by AI solutions.
• Provide domain expertise for the development and validation of AI/ML models, Generative AI solutions, agentic AI capabilities, decisioning solutions, and analytical use cases .
• Help establish appropriate business rules, controls, explainability requirements, and human-in-the-loop processes for AI-enabled insurance solutions.
• Ensure AI-generated outputs are evaluated against insurance business context and expected outcomes.

​ Domain Validation & Testing

• Partner with the Domain Validator to define business test scenarios, test scripts, expected results, and representative insurance test data.
• Leverage specifications as the foundation for requirements traceability and AI-assisted generation of test scenarios where appropriate.
• Ensure test coverage reflects real-world insurance scenarios, including normal, exception, boundary, and regulatory cases.
• Review functional test results and determine whether delivered capabilities satisfy business requirements.
• Coordinate with the Tech Validator and engineering teams when defects span business and technical concerns.
• Support business acceptance and provide domain-level recommendations for production readiness.

Insurance Domain Expertise

Candidates should have strong expertise in several areas of the insurance value chain, such as:

• Policy Administration — quote, bind, issue, endorsement, renewal, cancellation and reinstatement.
• Underwriting — risk assessment, appetite, eligibility, referrals, pricing and underwriting rules.
• Claims — FNOL, coverage verification, investigation, reserving, adjudication, settlement and recovery.
• Billing & Payments — premium billing, collections, commissions, refunds and reconciliation.
• Distribution — agents, brokers, direct channels, partner ecosystems and digital distribution.
• Product Management — product configuration, coverage, limits, deductibles, riders and product lifecycle.
• Customer & Servicing — customer/party management, service journeys, communications and omnichannel experiences.
• Insurance Data — policy, claims, customer, risk, exposure, product and reference/master data.
• Regulatory & Compliance — privacy, auditability, regulatory reporting, market conduct and jurisdiction-specific requirements.
• Experience may be concentrated in Property & Casualty, Life & Annuity, Commercial Insurance, Reinsurance , or a combination of these areas.

Knowledge and Attributes:

• Hands-on exposure to Generative AI and AI-assisted software development workflows .
• Experience using GitHub, GitHub Copilot, Claude Code, or equivalent AI development tools to collaborate with engineering teams.
• Experience with AI/ML, agentic AI, intelligent automation, advanced analytics, or decisioning solutions within insurance.
• Understanding of insurance data models, ontologies, semantic models, knowledge graphs, or related domain-modeling approaches.
• Experience modernizing legacy insurance platforms or implementing major insurance core systems.
• Familiarity with commercial insurance platforms and products such as Guidewire, Duck Creek, Majesco, Sapiens, Salesforce, or comparable insurance ecosystems.
• Experience working with cloud-native architectures and enterprise data platforms.
• Relevant insurance, architecture, agile, cloud, or technology certifications.

Academic Qualifications and Certifications:

• Bachelor's degree in business or marketing or a related field.
• Advanced degree such as an MBA is highly advantageous.

​Required experience:

• Typically 10+ years of insurance industry and/or insurance technology experience , with substantial experience in domain architecture, business architecture, solution consulting, product ownership, or a comparable role.
• Deep understanding of insurance business processes, operating models, products, and information flows.
• Demonstrated ability to translate complex business requirements into precise, structured, implementation-ready specifications .
• Understanding of AI-led, specification-driven software development practices and how specifications can drive implementation, testing, and validation.
• Familiarity with GitHub-based development environments, GitHub Copilot, Claude Code, or similar AI-assisted coding and agentic development tools .
• Ability to collaborate effectively with engineering teams using modern development workflows without necessarily being a hands-on software developer.
• Experience working across business, architecture, product, engineering, data, and testing organizations.
• Strong understanding of modern insurance technology landscapes, including core insurance platforms, APIs, integration patterns, cloud solutions, data platforms, and digital ecosystems.
• Experience developing user stories, functional specifications, business rules, process models, acceptance criteria, and test scenarios.
• Strong analytical and problem-solving capabilities with the ability to evaluate solutions from both business and technology perspectives.
• Excellent stakeholder management, facilitation, communication, and presentation skills.
• Ability to operate effectively in agile, iterative, prototype-driven, and AI-accelerated delivery environments.

Travel: majority will be regional within North America, and it is based on business needs. Client sites, team meetings, and industry events.

NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this remote role is $160K - $296K. This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on a number of factors, including the candidate’s actual work location, relevant experience, technical skills, and other qualifications. This position may also be eligible for incentive compensation based on individual and/or company performance.

This position is eligible for company benefits including medical, dental, and vision insurance with an employer contribution, flexible spending or health savings account, life and AD&D insurance, short and long term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally-required benefits.

Workplace type:

About NTT DATA
NTT DATA is a $30+ billion business and technology services leader, serving 75% of the Fortune

Global 100. We are committed to accelerating client success and positively impacting society through

responsible innovation. We are one of the world’s leading AI and digital infrastructure providers, with

unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and

application services. Our consulting and industry solutions help organizations and society move

confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more

than 70 countries. We also offer clients access to a robust ecosystem of innovation centers as well as

established and start-up partners. NTT DATA is part of NTT Group, which invests over $3 billion each

year in R&D.

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NTT DATA is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, colour, gender, sexual orientation, religion, nationality, disability, pregnancy, marital status, veteran status, or any other protected category. Join our growing global team and accelerate your career with us. Apply today.

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