Architecture Senior Advisor - Cigna Healthcare

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About the role

Lead AI Architect Purpose of this Role • The Lead AI Architect (AI) is responsible for defining, adopting, and assuring AI-enabled data architectures that are commercially viable, technically robust, and aligned to Cigna’s enterprise and data strategy. • As part of the International Health Global Architecture function, this role sets architectural direction and ensures strategic priorities are realised through data and AI delivery. • This role will drive innovation, productivity and operational improvements, and customer experience transformation by applying modern AI architecture in a secure, scalable, and responsible manner. • This role collaborates closely with business leaders, product teams, engineering, and third-party partners to ensure data and AI investments deliver measurable value while meeting regulatory, operational, and security requirements. Main Duties / Responsibilities Strategy & Architecture Leadership • Architect and own enterprise-scale Generative AI platforms supporting multiple business use cases, including internal pilots, automation assistants, knowledge discovery, and customer-facing AI experiences. • Define and maintain reference target-state data and AI architectures for International Markets, aligned to enterprise architecture standards and data strategy. • Act as a senior architectural authority for AI-enabled data solutions, ensuring consistency, reuse, and long-term sustainability across the landscape. • Advocate for AI-driven data design, embedding modern AI and analytics patterns into enterprise data platforms and services. • Maintain an active awareness of emerging trends in data architecture, AI/ML, and enterprise technology, assessing their potential impact and value for Cigna, advising senior leadership on AI strategy, feasibility and adoption paths. AI Architecture • Define architectural patterns and standards to support AI model lifecycle management, AI and data pipelines, feature engineering, and associated design artefacts. • Architect and own enterprise-scale Generative AI platforms supporting multiple business use cases, including internal pilots, automation assistants, knowledge discovery, and customer-facing AI experiences. • Define and maintain reference architectures and design patterns for LLM-based applications, covering model access, orchestration, retrieval, prompt management, evaluation, and observability. • Ensure that AI architectures support the needs of data science, analytics, and AI use cases, including scalability, performance, data quality, and governance. • Work with Solution Architects and engineering teams to translate business and technical requirements into coherent end-to-end data and AI solution designs. Delivery & Governance • Participate across the full delivery lifecycle, from early concept shaping and investment cases through to design assurance and governance during build and implementation. • Provide architecture governance through design reviews, standards definition, and participation in architecture review and approval forums. • Capture and manage architectural risks, issues, and assumptions, articulating their financial, operational, and delivery impacts. • Support sponsors in the creation of well-rounded and compelling business cases for data and AI-led change. Stakeholder & Commercial Leadership • Proactively engage with stakeholders across Business, IT, and third-party partners to ensure solutions are cost-effective, appropriate, and aligned to business outcomes. • Take a lead role in the selection and assessment of third-party data and AI solutions, establishing and maintaining effective supplier and partner relationships where required. • Apply strong commercial awareness, including financial planning, budgeting, and cost-b

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