Lead Insurance Domain Architect

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.