Cloud Engineering Lead Analyst

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.

Role Title : Cloud Engineering Lead Analyst

Position Summary :

You will be joining a team transforming healthcare and improving the lives and vitality of the millions of members we serve. We leverage cutting edge Artificial Intelligence (AI) and Machine Learning (ML) algorithms to develop solutions for automated document processing and customer service chat bots. We are looking for Sr AI Engineers with strong engineering, full stack expertise to evaluate new Large Language Models (LLMs) and make them available for the enterprise in a compliant and secure manner. The work you do will impact millions of customers, members, and employers that rely on Cigna every day. Extreme focus on speed to market and getting Products and Services in the hands of customers and passion to transform healthcare is key to the success of this role.

Job Description & Responsibilities :

• Build enterprise grade AI solutions with focus on privacy, security, fairness.
• Comprehensive understanding of cloud computing principles, services (such as resource pooling, rapid elasticity, measured service) and architectures(microservice and serverless) from major cloud providers (e.g., AWS, Azure, Google Cloud, OpenShift).
• Design and implement solutions leveraging OpenShift's features for container orchestration or using AWS services - Sagemaker, S3, Lambda, and EC2 to configure LLMs
• Test latest LLMs using standard evaluation criteria and make the LLMs available for enterprise use, with the right security, authentication, logging and monitoring.
• Efficiently managing cloud resources to optimize performance and cost.
• Architect and develop software or infrastructure for scalable, distributed systems and with machine learning technologies.
• Work with frameworks(Tensorflow, PyTorch) and open source platforms like Hugging Face to deliver the best solutions
• Optimize existing generative AI models for improved performance, scalability, and efficiency.
• Develop and maintain AI pipelines, including data preprocessing, feature extraction, model training, and evaluation.
• Develop clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.
• Contribute to the establishment of best practices and standards for generative AI development within the organization.

Experience Required :

Experience Desired :

Education and Training Required :

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