Job Description

About Evernorth Evernorth Health Services, a division of The Cigna Group (NYSE: CI), creates pharmacy, care, and benefits solutions to improve health and increase vitality. We relentlessly innovate to make the prediction, prevention, and treatment of illness and disease more accessible to millions of people. About Evernorth: Evernorth Health Services, a division of The Cigna Group (NYSE: CI), creates pharmacy, care, and benefits solutions to improve health and increase vitality. We relentlessly innovate to make the prediction, prevention, and treatment of illness and disease more accessible to millions of people. Position Overview: The Provider Technology Shared Services Engineering team is seeking an Software Engineer Lead Analyst for a Band 3 Contributor Career Track position. The Software Engineer Lead Analyst will play a critical role in system development within the broader Provider Technology Solutions and Engineering organization, significantly influencing Operations and Technology Product Management. This position will provide expertise in the engineering, design, installation and startup of automated systems, including a self-service onboarding kit that enables users to begin utilizing the solution within minutes. The solutions developed will be accessible to individuals with minimal technical skills and will require no additional coding, ensuring zero maintenance is needed. As a member of our team, you will operate within a high-performance, high-frequency enterprise technology environment. This role entails collaborating closely with IT management and staff to identify automated solutions that leverage existing resources with tailored configurations for each use case. The objective is to minimize redundancy in solutions while promoting an enterprise mindset focused on reusability and maintaining high standards, ultimately ensuring minimal future maintenance requirements. The Software Engineer Lead Analyst demonstrates significant creativity, foresight, and sound judgment in the conception, planning, and execution of initiatives. This role requires extensive professional knowledge and expertise to effectively advise functional leaders. Additionally, the Lead Analyst stays informed about the latest advancements in technology, including AI and machine learning, to enhance both existing and new automation solutions. These solutions are designed to optimize production costs while facilitating the addition or updating of features aimed at improving the overall software development lifecycle experiences. Responsibilities:

• Provide comprehensive consultation to business unit and IT management, as well as personnel, regarding all facets of application development, testing and automation solutions across diverse development, financial, operational, and computing environments.
• Offers leadership and strategic vision in architectural design and AI/ML guidance for the team.
• Perform comprehensive research to identify and recommend the most efficient, cost-effective, and scalable AI/ML automation solutions applicable throughout the Software Development Life Cycle (SDLC). This includes areas such as test data generation, code generation, test case generation, test script generation, root cause analysis, predictive analysis, etc., with the aim of enhancing the overall SDLC from development to production support.
• Ensures that engineering solutions are aligned with the overall Technology strategy while addressing all application requirements.
• Demonstrate industry-leading technical abilities that enhance product quality and optimize day-to-day operations.
• Understand how changes impact work upstream and downstream including various back-end and front-end architectural modules.
• Enhance personnel effectiveness using heat matrices to prioritize Quality and Development Engineering resources on high-impact interfaces while identifying areas of lesser focus.
• Proactively monitor and manage the design of supported automation solutions, ensuring scalability, stability, flexibility, simplicity, performance, availability, security, and capacity.
• Develop and implement automation solutions to improve engineering and operational efficiency.
• Troubleshoot and optimize automated solutions and related artifacts to ensure seamless execution in CI/CD pipelines and on local machines, minimizing software and package dependencies or conflicts to reduce cycle time.
• Execute on a strategy to hand over the automation solutions to every Agile teams for adoption and use within their areas of focus, requiring zero maintenance and minimal effort for any enhancements without delving into coding.
• Encouraging and building automated processes wherever possible.
• Recognized internally as a subject matter expert.

Required Skills:

• Foundations in Machine Learning and Deep Learning: Understanding algorithms, neural networks, supervised and unsupervised learning, and deep learning frameworks like TensorFlow, PyTorch, and Keras.
• Generative Models: Knowledge of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers.
• Natural Language Processing (NLP): Knowledge in NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face Transformers) for text generation tasks.
• Model Deployment: Experience with deploying models using services like TensorFlow Serving, TorchServe, or cloud-based solutions (e.g., AWS SageMaker, Google AI Platform).
• Basic understanding of implementing Prompt Engineering, Finetuning and RAG.
• Strong foundation and practical experience in programming languages, especially Python, within the context of AI/ML workflows, crucial for transitioning from traditional software development processes to optimized and innovative solutions that enhance market agility.
• Containerization and Orchestration: Experience with Docker and Kubernetes / OpenShift for containerization and orchestration of applications.
• CI/CD Pipelines: Knowledge of continuous integration and continuous deployment tools and practices.
• Security Best Practices: understanding of security principles and best practices for protecting data and systems, including IAM, encryption and network Security.
• Cloud Services: Familiarity with cloud platforms like AWS / Google Cloud / Azure for deploying and managing applications and AI models.

Required Experience & Education:

• A Bachelor