Software Engineering Lead Analyst - HIH - Evernorth at Cigna Healthcare

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

04 Aug, 26

Salary

0.0

Posted On

06 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PyTorch, TensorFlow, Large Language Models, RAG Systems, AWS SageMaker, Databricks, Data Preprocessing, Feature Engineering, Neo4j, Knowledge Graphs, MLOps, GPU Acceleration, Distributed Computing, AI/ML Model Design, Machine Learning Algorithms

Industry

Hospitals and Health Care

Description

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. Position Overview We're seeking a talented AI/ML Engineer to design, develop, and deploy cutting-edge AI and machine learning solutions. You'll work with state-of-the-art models and technologies, contributing to projects that have the potential to revolutionize industries. Roles & Responsibilities Design and implement AI/ML models using various frameworks and libraries. Work with large language models (LLMs) from providers like OpenAI and AnthropicDevelop and optimize RAG (Retrieval-Augmented Generation) systems. Collaborate with cross-functional teams to integrate AI capabilities into our applications. Conduct experiments and analyze results to improve model performance. Stay updated with the latest advancements in AI/ML and propose innovative solutions Qualifications Required Experience & Skills: 6 to 8 years of development experience. Strong proficiency in Python and AI/ML libraries (e.g., PyTorch, TensorFlow). 5+ years of experience working with large language models (e.g., GPT-4, Claude). Familiarity with RAG systems and related technologies. Strong understanding of machine learning concepts and algorithms. Experience with cloud-based ML platforms (e.g., AWS SageMaker, Databricks)Proficiency in data preprocessing and feature engineering Preferred Experience & Skills: Advanced degree in Computer Science, AI, or a related field. Experience with graph databases (e.g., Neo4j) and knowledge graphs. Familiarity with MLOps practices and tools. Experience with GPU acceleration and distributed computingContributions to AI/ML open-source projects or research publications Equal Opportunity Statement Evernorth is an Equal Opportunity Employer actively encouraging and supporting organization-wide involvement of staff in diversity, equity, and inclusion efforts to educate, inform and advance both internal practices and external work with diverse client populations. About Evernorth Health Services Evernorth Health Services, a division of The Cigna Group, creates pharmacy, care and benefit 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. Join us in driving growth and improving lives. Doing something meaningful starts with a simple decision, a commitment to changing lives. At The Cigna Group, we’re dedicated to improving the health and vitality of those we serve. Through our divisions Cigna Healthcare and Evernorth Health Services, we are committed to enhancing the lives of our clients, customers and patients. Join us in driving growth and improving lives.

Responsibilities

Design, develop, and deploy cutting-edge AI and machine learning solutions, specifically focusing on LLMs and RAG systems. Collaborate with cross-functional teams to integrate these AI capabilities into applications and optimize model performance.