The Cigna Group's Technology Development Program - AI Engineering Track Summer Internship

The Cigna Group’s Technology Development Program (TECDP) Generative AI Internship Get ready to embark on an exhilarating summer adventure with The Cigna Group’s Technology Development Program Summer Internship! We are on the lookout for passionate individuals who are eager to dive into the world of technology and make a real difference in healthcare. Over the course of 12 dynamic weeks, you’ll have the chance to work on impactful technology projects, receive comprehensive training, and benefit from invaluable mentorship that will supercharge your career.

What You Will Do

Meaningful Work: Contribute within the Artificial Intelligence track by building impactful technical solutions that drive innovation across The Cigna Group while strengthening your real-world skills. Learn by Collaborating: Learn by doing alongside peers, mentors, and cross-functional partners through hands-on projects, recruiting support, innovation efforts, community initiatives, and onboarding experiences. Structured Learning: Grow through a blend of core and track-specific curriculum, including technical training, leadership development, and business exposure to support your development as a well-rounded technologist. Community & Connection: Build strong relationships across the organization through networking, mentorship, cross-functional collaboration, and informal peer engagement that support both personal and professional growth.

Qualifications

What you need to do the job

Must be currently pursuing a degree in Computer Science, Data Science, Artificial Intelligence, or a related field, with a strong emphasis on machine learning methodologies and applications. Foundational understanding of machine learning concepts, including supervised and unsupervised learning techniques, with experience applying them through coursework, projects, research, or prior experience. Working knowledge of Python and exposure to machine learning or generative AI libraries and frameworks such as Scikit-Learn, Tenso