AI Business Partner Senior Principal
Cigna Healthcare
Role Purpose The Senior Principal AI Business Partner (AIBP) is a senior technical and product leader who shapes AI investment, portfolio prioritization, and delivery standards across business units. This role combines executive problem framing with enterprise solution design—setting direction for complex, multi-stakeholder AI programs while remaining credible in architecture and early-stage delivery. Senior Principal AIBPs operate at portfolio and cross-BU scope: they align SBU sponsors, technology leaders, and AI IO delivery teams on where to invest, how to structure engagements, and how to scale what works. They mentor Principal AIBPs and contribute reusable patterns to the enterprise AI operating model. AI-native practice is expected at a leadership level—spec-driven development, agentic tooling, and the judgment to know when to engage hands-on versus when to orchestrate teams and forums. Enterprise Problem Framing & Portfolio Prioritization
- Partner with SBU executive sponsors and functional leadership across domains to identify fundamental business problems with enterprise-scale AI potential.
- Frame AI opportunities with financial, strategic, and technical rigor to enable confident investment decisions at portfolio and SteerCo forums.
- Stack-rank and socialize AI initiatives across the portfolio based on value potential, feasibility, execution risk, and strategic alignment.
- Enterprise AI Solution Design & Standards
- Engage CIOs and technology leaders as a credible AI solution architect—contributing to architectural decisions, trade-off analysis, and solution design for the most complex initiatives.
- Define and evolve reusable AI patterns, engagement models, and reference architectures adopted across AIBPs and delivery teams.
- Shape enterprise build, buy, and adapt decisions with accountability for scale, security, and responsible AI.
- contribute to hiring bar, onboarding, and capability development for the AIBP function.
- Communicate progress, risk, and impact to C-suite and technology executive stakeholders.
- Champion adoption of enterprise AI frameworks, governance, and best practices across business and technology teams.
- Formal education in engineering, computer science, data science, or related field
- Professional training in AI/ML
- Hands-on experience building AI or data-intensive systems
- Proven experience working in an AI-first way, actively using modern agentic development tools.
- Senior product management, product engineering, or technical program leadership experience—from executive narrative to portfolio outcomes and shipped solutions at scale. Experience partnering with engineering and data science leaders as a technical peer and thought partner.
- Financial and analytical acumen to assess portfolio-level value, trade-offs, and execution risk.
- Typically 12+ years of relevant experience, including leading AI or digital initiatives in complex enterprise environments.
- Experience spanning multiple business units, domains, or enterprise portfolio governance.
- Familiarity with LLM application design, enterprise AI architecture patterns, and responsible AI principles at scale.
- Track record of taking multiple AI initiatives from POC to production and transitioning ownership to business operations.
- AI-Native Technical Leadership: Deep practitioner understanding plus judgment on when and how to apply AI at enterprise scale.
- Executive Problem Framing: Identifies enterprise-worthy problems and structures AI opportunities for investment forums.
- Balances value, feasibility, risk, and capacity across a multi-initiative portfolio.
- The enterprise AI portfolio is prioritized, visible, and progressing with clear ownership and value tracking.
- Complex POCs and pilots reach production with measurable business impact and clean transition paths.
- Enterprise AI frameworks and AI-first practices are adopted consistently across business units.
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