Software Engineering Lead Analyst

1 day ago

Hyderabad, Telangana, India Evernorth Full time

Software 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 build the best fit solutions leveraging Large Language Models (LLMs) and Generative AI solutions. 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

Responsibilities:

Build scalable software solutions using LLMs and other ML models to solve challenges in healthcare

Build enterprise grade AI solutions with focus on privacy, security, fairness.

Work with Product Development as a Generative Artificial Intelligence (AI) subject matter expert and architect and develop scalable, resilient, ethical AI solutions

Strong engineering skills to design the output from the AI with nodes and nested nodes in JSON or array, HTML formats as required This is critical so that the AI output can be consumed as is and displayed on the dashboard for accelerated development cycles.

Build extensible API Integrations, low code UI/UX solutions, with extremely short cycle times, to extract information from sources, integrate with GPT4, receive insights and make them available in intuitive, high performing dashboards Build solutions that align with responsible AI practices.

Envision the solution outcomes to solve for the business problem with actionable insights and design viable solutions to meet the outcomes.

Understand how AI is interpreting the data set and use that understanding to build prompts that lead to expected outcomes

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.

Strong technical skills in machine learning and AI, especially natural language processing, generative models like GPT-3, DALL-E, etc. Understanding how these models work is crucial.

Solid delivery experience of at least one large scale solution leveraging Gen AI.

Experience with large-scale cloud infrastructure and services like AWS, GCP, Azure. Knowing how to build and deploy AI solutions leveraging cloud services.

Software engineering skills - Ability to build systems and infrastructure to deploy AI models into production applications and ensure effective integration.

Knowledge of AI Responsibility principles like safety, transparency, fairness and accountability. Assessing and mitigating risks from generative AI.

Architectural design ability - Design effective pipelines, processes, validation mechanisms for building enterprise-grade generative AI solutions.

Understanding of various applications of generative AI like summarization, translation, conversational systems, retrieval augmented generation

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.

Required Skills:

proficient in python and commonly used data science libraries like pandas, scikit learn, tensorflow, keras, PyTorch etc. (some of these libraries)

Experience working with different LLMs and Proficient in Prompt Engineering.

Experience building machine learning infrastructure, data pipelines to train ML models

experience with common machine learning techniques like pre-processing data, training, evaluation of models

experience with public cloud technologies and their ML services (AWS preferred)

Required Experience & Education:

Degree in Computer Science, Artificial Intelligence, or a related field

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