AI Quality Enablement Engineer - Cigna Healthcare

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.

You’ll join a globally recognized organization where trust, clear communication, and a positive culture shape how we work. Our leaders are consistent, approachable, and supportive, helping you maintain balance while doing meaningful work. We look for people who thrive in collaborative environments, care about meaningful change, and want to grow in a company that puts people first. At Cigna Healthcare, your work contributes to better care experiences and supports customers through important moments in their lives.

You will help accelerate the adoption of AI-enabled practices across Quality Engineering, enabling teams to improve quality, automation, productivity, and delivery outcomes. Working closely with Scrum teams, you will identify opportunities to apply AI across the Quality Engineering lifecycle and support the practical implementation of solutions that drive measurable improvements in efficiency, scalability, and engineering effectiveness.

• Drive adoption of AI-enabled Quality Engineering practices to improve quality, automation, scalability, operational efficiency, and engineering effectiveness.
• Define standards, guidance, best practices, and guardrails that support the effective and responsible use of AI within Quality Engineering activities.
• Design, develop, prototype, and evaluate AI-enabled solutions, accelerators, workflows, templates, and Proofs of Concept that enhance testing, automation, analysis, reporting, and knowledge management.
• Integrate AI tools and capabilities into Quality Engineering processes to improve testing effectiveness, engineering productivity, and delivery outcomes.
• Partner with Scrum teams to identify opportunities for continuous improvement across quality, automation, CI/CD adoption, and modern Quality Engineering practices.
• Monitor and report on adoption, utilization, and business outcomes through KPIs, dashboards, scorecards, and quality performance measures.
• Facilitate workshops, training sessions, knowledge-sharing activities, and cross-functional improvement initiatives that build AI capability across teams.

• Strong understanding of Quality Engineering principles, methodologies, frameworks, and industry best practices.
• Strong understanding of AI, Generative AI, prompting techniques, AI-assisted software development, and AI-enabled Quality Engineering practices.
• Experience evaluating, implementing, or enabling AI-driven solutions that improve Quality Engineering, automation, productivity, and quality outcomes.
• Experience designing, developing, prototyping, or implementing AI-enabled solutions, automations, accelerators, integrations, or related capabilities within Quality Engineering or software delivery environments.
• Strong understanding of Agile, Dev Ops, CI/CD, and modern Quality Engineering practices.
• Experience defining standards, governance approaches, frameworks, guardrails, or best practices, while influencing outcomes across multiple Agile delivery teams.

• Stakeholder management and relationship building
• Clear communication and facilitation skills
• Influencing and collaboration across cross-functional teams
• Analytical thinking and problem-solving
• Continuous improvement mindset
• Knowledge-sharing and enablement capabilities

• Quality…