IT Senior Principal

This position within the AI Center of Enablement represents the most distinguished technical role within The Cigna Group, operating at the intersection of cutting-edge research, enterprise-scale engineering, and business strategy to shape the future of AI technology both within the enterprise and across the broader healthcare industry. The AI Engineering Senior Principal transcends traditional engineering leadership to define the organization's AI capabilities for the next decade, making decisions that establish the technical identity of Cigna's AI capabilities in the broader industry landscape. This role establishes the 10 year vision for AI engineering capabilities anticipating multiple technology paradigm shifts, architects next-generation AI platforms that enable capabilities not yet imagined by the business, identifies breakthrough AI research with transformational business potential months before mainstream awareness, and drives cultural transformation in how the organization approaches AI development and deployment. The Senior Principal is recognized as a preeminent expert in AI engineering, influencing not only internal technical direction but contributing to the evolution of the field itself through research publications, industry standards participation, and thought leadership, ultimately positioning The Cigna Group as a leader in healthcare AI innovation while improving the cost, quality and access to healthcare for Cigna's clients and customers. As an AI Engineering Senior Principal, you will engage at the highest organizational levels including C-suite executives and board members, driving alignment between technical strategy and business strategy with multi-year impact. You will architect technical foundations that remain relevant through multiple waves of AI innovation, establish research partnerships with leading universities and AI companies, drive adoption of breakthrough technologies providing sustained competitive advantage, and influence AI product roadmaps of major vendors through strategic partnerships. This role requires the highest levels of influence within the business, technology and architecture organizations equivalent to C-suite executives, extensive business and domain knowledge across healthcare operations, innovative problem-solving skills operating years ahead of mainstream AI adoption, and the ability to marry business and technology into a cohesive value-oriented strategy that positions the organization as an industry leader in AI capabilities. DUTIES & RESPONSIBILITIES: + Define the 10 year vision for AI engineering capabilities, anticipating multiple technology paradigm shifts in healthcare AI + Shape the organization's fundamental approach to AI, establishing principles that outlast specific technologies + Drive decisions on which emerging AI capabilities become core organizational competencies versus external partnerships + Establish the technical identity of the organization's AI capabilities in the broader healthcare and technology industry landscape + Serve as technical counsel to C-suite executives and board members on AI strategy, risk, and opportunity + Influence enterprise business strategy by identifying transformational applications of AI technology to healthcare delivery, operations, and member experience + Lead technical due diligence for major strategic decisions including M&A, partnerships, and technology investments + Architect next-generation AI platforms that enable healthcare capabilities not yet imagined by the business + Design technical foundations using Python, AWS, Terraform, and emerging technologies that remain relevant through multiple waves of AI innovation + Create abstractions and frameworks that accelerate development velocity by 100x while maintaining quality, safety, and HIPAA compliance + Build AI infrastructure that scales from proof-of-concept to enterprise production across thousands of healthcare applications + Design systems that seamlessly integrate future AI modalities including multimodal models, embodied AI, and neuromorphic computing + Create platforms that democratize AI capabilities across the organization while maintaining governance and control + Identify breakthrough AI research with transformational business potential months before mainstream awareness + Design experiments to validate feasibility of emerging techniques at enterprise scale + Build pathways to operationalize research concepts into production systems serving millions of healthcare members + Develop novel AI engineering approaches that combine multiple research breakthroughs in unique ways + Create proprietary AI capabilities that provide sustained competitive advantage in healthcare markets + Establish research partnerships with leading universities, labs, and AI companies (OpenAI, Anthropic, academic institutions) + Publish research-level technical papers that advance the state of AI engineering practice in healthcare + File patents on novel AI architectures, algorithms, and systems + Lead open-source initiatives that influence how the industry builds AI systems + Present keynote addresses at premier AI and engineering conferences + Serve on technical advisory boards for AI startups, research institutions, and standards bodies + Contribute to AI safety, ethics, and governance standards at industry and regulatory levels + Build relationships with AI research leaders and influence direction of AI technology evolution + Drive cultural transformation in how the organization approaches AI development and deployment + Establish engineering excellence standards that elevate technical capabilities across hundreds of engineers + Create technical career frameworks and mentorship programs that develop future AI engineering leaders + Build mechanisms for rapid technology adoption and continuous organizational learning + Lead initiatives to modernize legacy technical debt and establish modern AI engineering practices using GitHub, containerization, infrastructure-as-code, and cloud-native architectures + Define technical standards, patterns, and practices that govern AI development across the organization + Chair enterprise architecture review boards for the most critical AI initiatives + Make final technical decisions on contentious issues with organization-wide implications + Establish quality gates and technical controls that balance innovation velocity with risk management + Develop compliance frameworks that satisfy healthcare regulatory requirements (HIPAA, FDA) while enabling innovation + Cultivate relationships with AI model providers (OpenAI, Anthropic, Mistral) to influence product roadmaps + Engage with cloud providers (AWS) to shape AI infrastructure offerings + Build partnerships with AI startups to gain early access to breakthrough technologies + Participate in industry consortiums defining AI standards and best practices + Represent the organization in regulatory discussions about AI policy and governance in healthcare + Own availability, cost, and performance of AI infrastructure processing billions of requests annually + Design resilient systems that maintain service through model provider outages, API changes, and infrastructure failures + Establish automated evaluation frameworks that continuously monitor quality across hundreds of models and applications + Create observability platforms using Langsmith and custom tools providing unprecedented visibility into AI system behavior and business impact + Implement cost optimization strategies that reduce infrastructure spend by millions annually while improving performance + Design security architectures that protect against sophisticated adversarial attacks and data exfiltration + Drive programs, initiatives and projects up and down the organizational hierarchy and support RFPs and client presentations by providing business-facing architectural input and ensuring enterprise mindset is present at the highest strategic levels REQUIRED QUALIFICATIONS: + Bachelor's degree in Software Engineering, Computer Science, Engineering, Mathematics, Physics, or related technical field required + 15+ years of software engineering experience with at least 8 years building production AI/ML systems at massive scale + Recognized industry expert in AI engineering with speaking engagements, publications, or major open-source contributions + Deep experience architecting AI platforms supporting thousands of engineers or millions of end users + Comprehensive expertise across the entire AI stack from model training to production deployment + Mastery of multiple programming languages, frameworks, and technology stacks with ability to evaluate emerging technologies + Expert understanding of LLM architectures with knowledge extending to model training, fine-tuning, and optimization + Deep expertise in advanced AI techniques including multimodal models, agentic systems, and emerging paradigms + Comprehensive knowledge of distributed systems, cloud architecture (AWS), and platform engineering at hyperscale + Deep understanding of transformer architectures, attention mechanisms, and future directions in neural network research + Expertise in model training including distributed training, RLHF, constitutional AI, and alignment techniques + Advanced knowledge of inference optimization including quantization, distillation, speculative decoding, and hardware acceleration + Comprehensive understanding of AI safety, alignment, interpretability, and robustness + Expertise in AI evaluation methodologies, benchmark design, and quality assurance frameworks + Deep knowledge of AI ethics, fairness, bias detection, and responsible AI practices particularly in healthcare contexts + Understanding of healthcare regulatory landscape (HIPAA, FDA) and ability to anticipate future AI governance requirements + Proven track record of defining technical strategy that shaped organizational capabilities for years + History of leading transformational initiatives affecting thousands of people and millions of dollars in value + Demonstrated ability to influence technical decisions at the highest organizational levels + Extensive experience mentoring senior technical leaders and developing organizational talent + Published research, patents, or major open-source contributions recognized by the broader industry + Speaking engagements at premier conferences with recognition as a thought leader + External recognition through awards, advisory positions, or industry influence + Track record of making high-stakes decisions with incomplete information in rapidly evolving domains + Deep understanding of how technology enables business strategy and competitive advantage in healthcare + Ability to translate technical capabilities into business value and communicate to non-technical executives + Experience participating in board-level discussions and strategic planning + Understanding of organizational dynamics and change management at scale + Capability to assess market dynamics, competitive positioning, and technology trends + Skill in building business cases for multi-million dollar technology investments + Strong leadership, collaboration, and negotiation skills at the executive level; able to lead by influence and build consensus among C-suite peers + Knowledge of IT strategic planning and capability development; experience implementing technology strategy and roadmaps at enterprise scale + Deep understanding of AI and Generative AI technology frameworks and tools, and common patterns and best practices with their applications to healthcare business operations + Self-directed and execution focused with a

Created: 2025-11-21