Lead AI Architect

About Cigna Healthcare

Cigna Healthcare is a global health service company dedicated to transforming healthcare. With roots in the U.S. and operations in over 30 countries we serve more than 180 million customers and patients worldwide. Ranked 13th on the Fortune 500 in 2025 Cigna is recognized as one of the most trusted and influential names in the industry.

Our mission is to improve the health well-being and peace of mind of those we serve.

Join our globally recognized brand where trust communication and a positive culture are at the core of everything we do. Our leadership is consistent approachable and supportive-ensuring your well-being and work-life balance.

Were looking for individuals who thrive in collaborative environments are passionate about meaningful change and want to grow in a company that puts people first.

At Cigna youll be part of a purpose-driven team that values innovation compassion and impact. Whether youre shaping better care experiences or supporting customers through lifes key moments your work will matter.

Grow with us-and help shape the future of healthcare.

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 Cignas 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-benefit considerations in architectural decision-making.

Capability Building & Mentoring

• Provide high-level mentoring and guidance to architects design and development teams to embed data and AI principles standards and best practices.
• 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.
• Contribute to the maturity of Cignas data and AI architecture capability through knowledge sharing standards development and continuous improvement.
• Apply strong commercial awareness including financial planning budgeting and cost-benefit considerations in architectural decision-making.

Skills & Experience

Essential Experience

• Demonstrated expertise in architecting and leading large-scale AI initiatives taking solutions from proof of concept through to successful production deployment.
• Deep understanding of architectural considerations and trade-offs in AI and machine learning projects built through hands-on delivery experience.
• Experience working effectively within globally distributed teams and complex stakeholder environments.

Generative AI & Core Concepts:

• Large Language Models (LLMs) embeddings prompt engineering - Retrieval-Augmented Generation (RAG) Knowledge bases and Multimodal embeddings
• Agentic AI workflows and tool calling - Model Context Protocol (MCP) concepts and context management
• Knowledge on foundational models and inference profiles regional hosting and restrictions of various models and be able to identify the right model for the right requirements.

AI Architecture & Tooling

• Awareness of AI Gateway / model access layer design and access controls on the gateways.

• Proficiency in designing and implementing AI Gateway/model access layers to facilitate secure and scalable access to AI models.
• Experience in architecting solutions with vector databases and semantic search for efficient retrieval of information from large volumes of unstructured data.
• Skilled in leveraging document intelligence platforms (e.g. Azure Form Recognizer AWS Textract Google Document AI) for document classification data extraction and entity recognition from varied formats including scanned documents PDFs and handwritten forms.
• Knowledge of Intelligent Document Processing (IDP) solutions for automated ingestion parsing and validation of unstructured documents ensuring accurate routing of documents to appropriate business workflows.
• Familiarity with workflow orchestration frameworks (such as LangChain LangGraph or equivalent) to automate end-to-end document processing pipelines including document routing exception handling and integration with downstream systems.
• Understanding of optical character recognition (OCR) natural language processing (NLP) techniques and entity linking for extracting actionable insights from diverse data types.
• Awareness of data validation quality checks and document lifecycle management best practices to ensure compliance and reliability in document processing solutions.

• End-to-end AI pipelines: ingestion retrieval generation evaluation and rollout.
• Familiarity with AI governance model lifecycle considerations and responsible use of data and AI particularly within regulated environments.

Qualifications

• Advanced degree inComputer Science Artificial Intelligence Machine Learning or a related field.
• 10 yearsof experience building and architecting large-scale software or AI systems in medium-to-large enterprises.
• 5 yearsof experience withAI/ML NLP or Generative AI
• Experience working inregulated or compliance-sensitive environments(e.g. healthcare finance insurance global enterprises).
• Strong communication skills with the ability to influence technical and non-technical stakeholders with English at C2 level.

Why Youll Love Working here

• Competitive salary

• Multicultural and hybrid working environment

• Private Medical Insurance

• Employee Wellbeing Benefits

• Educational Development Program

About Cigna Healthcare

Qualified applicants will be considered without regard to race color age disability sex childbirth (including pregnancy) or related medical conditions including but not limited to lactation sexual orientation gender identity or expression veteran or military status religion national origin ancestry marital or familial status genetic information status with regard to public assistance citizenship status or any other characteristic protected by applicable equal employment opportunity laws.

If you require reasonable accommodation in completing the online application process please email: for support. Do not email for an update on your application or to provide your resume as you will not receive a response.