ABOUT EVERNORTH:
Evernorth exists to elevate health for all, because we believe health is the starting point for human potential and progress. As champions for affordable, predictable and simple health care,
we solve the problems others don't, won't or can't. Our innovation hub in India will allow us to work with the right talent, expand our global footprint, improve our competitive stance, and better deliver on our promises to stakeholders. We are passionate about making healthcare better by delivering world-class solutions that make a real difference.
We are always looking upward. And that starts with finding the right talent to help us get there.
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 customer 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:
- 5 years of AWS services - Sagemaker, S3, Lambda, and EC2 to configure LLMs, configuring and deploying cloud services, setting up authentication, monitoring and logging
- 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects
Experience Desired:
- Experience in implementing enterprise systems in production setting for AI, computer vision, natural language processing. Exposure to self-supervised learning, transfer learning, and reinforcement learning is a plus.
- Experience with information storage / retrieval using vector databases like pinecone.
- Experience with designing scalable software systems for classification, text extraction / summary, data connectors for different formats(pdf, csv, doc, etc)
- Experience with machine learning libraries and frameworks such as PyTorch or TensorFlow, Hugging Face, Lang chain, Llama Index.
Education and Training Required:
- Degree in Computer Science, Artificial Intelligence, or a related field.
Primary Skills:
- OpenShift and Kubernetes Expertise: In-depth knowledge of OpenShift and Kubernetes concepts, architecture, and best practices
- Programming experience in C / C++, Java, Python.
- Good to have Web development and solution skills, Flask, Django (for Python) or Express (for Node.js) Basic knowledge of web frameworks for creating restful APIs to serve models as a service.
- AWS Services knowledge: Leveraging one or more of Sagemaker, S3, Lambda, and EC2 to build solutions on the AWS cloud
Additional Skills:
- Strong knowledge of data structures, algorithms, and software engineering principles.
- Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure.
- Excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions.
- Strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.
- Possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment
