Software Engineering Senior Director - Evernorth - Hybrid

Cigna Healthcare•Morris Plains, NJ

2d•Hybrid

About The Position

We are seeking an experienced and visionary technology leader to guide software delivery, product strategy, and technology planning for Evernorth Health Systems Services Technology, supporting our Coverage Review and Population Health organizations. This leader will play a critical role in scaling modern, resilient technology platforms while developing strong engineering teams and partnering closely with business leaders across the enterprise. This role offers the opportunity to shape strategy, influence change, and lead innovation across a rapidly growing footprint within Evernorth and The Cigna Group. If you are energized by complexity, collaboration, and building technology that matters, this is a chance to make a meaningful and lasting impact.

Requirements

Minimum of 15 years of relevant experience in technology delivery, software engineering, and product leadership, including people management.
Demonstrated ability to lead large, complex technology portfolios and teams through transformation and growth.
Proven experience influencing and partnering with senior‑level business and technology leaders.
Strong understanding of enterprise software engineering practices, architecture, and delivery at scale.
Healthcare domain knowledge, with experience supporting regulated or mission‑critical platforms.
Demonstrated success driving innovation, automation, and AI enabled solutions in enterprise environments.
Excellent written, verbal, and presentation skills, with the ability to communicate complex topics clearly.
Willingness to travel up to 30% and flexibility to support business needs.

Nice To Haves

Bachelor’s degree in engineering, technology, or a related field.
Experience in pharmacy, healthcare services, or distribution‑based industries.
Experience leading globally distributed teams across multiple sites.
Strong background in agile delivery models, portfolio management, and large‑scale transformation initiatives.
Demonstrated success driving innovation, automation, and AI‑enabled solutions in enterprise environments.

Responsibilities

Set and deliver short‑ and long‑term technology vision for Coverage Review and Population Health, aligning product, architecture, and delivery strategies to business outcomes.
Lead, engage, and develop engineering leaders and teams, creating an inclusive, high‑performance culture grounded in accountability, growth, and innovation.
Own end‑to‑end technology delivery and product accountability, including deep understanding of system architecture, business transactions, automation opportunities, and upstream and downstream dependencies.
Partner closely with senior business leaders, attending staff meetings and serving as a trusted advisor to influence strategy, roadmaps, and investment decisions.
Build and evolve global delivery capabilities, including establishing and scaling teams in off shore locations to strengthen innovation and reduce vendor dependency.
Define staffing and financial plans for the product domain, including budget ownership, performance management, and talent development strategies.
Drive future‑state architecture and roadmaps, ensuring solutions are scalable, resilient, secure, and aligned with enterprise standards.
Champion innovation and continuous improvement, proactively identifying automation opportunities and introducing AI‑enabled solutions where appropriate.
Manage total cost of ownership, partnering with finance to meet budget commitments and build strong business cases for major technology investments.
Collaborate across the enterprise, strengthening alignment with architecture, security, audit, operations, product, and portfolio management partners.
Advocate modern engineering practices, including agile delivery, strong engineering patterns, resiliency‑focused design, and emerging technology trends.
Remove organizational and technical barriers, enabling teams to meet quality standards, delivery commitments, and business objectives.
Drive AI-enabled engineering productivity, apply AI tools across coding, testing, and support to accelerate delivery and improve quality
Identify high-impact AI use cases that reduce manual effort and enhance decision-making
Establish measurable engineering outcomes by defining and tracking clear metrics and use data to continuously improve productivity, quality, and predictability
Create transparency through shared metrics and insights and use metrics to drive accountability, prioritization, and leadership decisions