IT Principal

This position within the AI Center of Enablement represents the apex of technical leadership for AI engineering across The Cigna Group, defining the future of AI engineering capabilities and making critical technical decisions with multi-year impact. The AI Engineering Principal serves as the organization's foremost authority on AI platform engineering, combining unparalleled technical depth with strategic vision, organizational influence, and the ability to drive transformational change in how the enterprise builds and deploys AI systems.

This role establishes multi-year technical strategy for AI platform evolution, architects foundational platforms enabling hundreds of use cases, drives adoption of emerging AI paradigms across the enterprise, and shapes technical standards that influence hundreds of engineers and thousands of AI applications. The Principal shapes not only what the organization builds but how it builds, solving novel technical problems that lack industry precedent and building capabilities that differentiate the organization from competitors, ultimately helping improve the cost, quality and access to healthcare for Cigna's clients and customers for years to come.

As an AI Engineering Principal, you will engage broadly across Enterprise Architecture, Technology, Business Operations, and executive leadership, driving alignment of technical strategy with business objectives. You will design enterprise-wide AI infrastructure that balances innovation velocity, reliability, security, and cost, establish reference architectures that become organizational standards, lead transformational initiatives to modernize AI systems, and translate cutting-edge AI research into production engineering practices months before industry adoption.

This role requires the highest levels of influence within the business, technology and architecture organizations, extensive business and domain knowledge, innovative problem-solving skills operating at the frontier of AI technology, and the ability to marry business and technology into a cohesive value-oriented strategy that guides the organization's AI capabilities for the next 3-5 years.##

DUTIES & RESPONSIBILITIES:

* Define multi-year technical strategy for AI platform evolution, anticipating technology shifts and business needs
* Drive fundamental architectural decisions that shape the enterprise's AI capabilities for years to come
* Identify and champion strategic technology investments that provide sustainable competitive advantage in healthcare AI
* Establish technical principles and philosophies that guide AI engineering across the organization
* Serve as principal technical advisor to executive leadership on AI engineering strategy, feasibility, and risk
* Architect and drive implementation of foundational AI platforms that enable hundreds of healthcare use cases
* Design enterprise-wide AI infrastructure on AWS that balances innovation velocity, reliability, security, HIPAA compliance, and cost optimization
* Establish reference architectures and design patterns using Python, FastAPI, Pydantic, Terraform, and Podman that become standards across the organization
* Create frameworks that abstract complexity and accelerate AI application development by 10x
* Design sophisticated multi-model orchestration platforms that dynamically optimize across dozens of LLMs and SLMs using LiteLLM and custom routing logic
* Architect enterprise-scale RAG systems incorporating neo4j graph databases, vector stores, knowledge graphs, and intelligent retrieval strategies
* Build advanced agent frameworks supporting tool use, reflection, planning, and multi-agent collaboration
* Implement cutting-edge techniques including model distillation, fine-tuning pipelines, synthetic data generation, and evaluation frameworks
* Create observability platforms providing deep visibility into model behavior, performance, and cost using Langsmith and custom instrumentation
* Architect cost optimization systems that reduce AI infrastructure spend by 50%+ through intelligent routing, caching, and resource management
* Build security and compliance frameworks for AI systems addressing prompt injection, data leakage, adversarial attacks, and HIPAA requirements
* Conduct research-level investigations into emerging AI capabilities and their enterprise healthcare applications
* Translate cutting-edge AI research into production engineering practices months before industry adoption
* Develop novel AI engineering techniques that solve unique enterprise healthcare challenges
* Publish technical papers, patents, and open-source contributions that advance the field
* Present at major industry conferences and represent the organization as an AI engineering thought leader
* Build relationships with AI vendors (OpenAI, Anthropic, Mistral), research institutions, and technology partners
* Set technical standards and engineering practices that impact hundreds of engineers using Git Hub, containerization, and infrastructure-as-code
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