AI Engineer III

• The AI Engineer III is responsible for advanced analytics applying statistical, mathematical, and computational models to diverse datasets to solve clinical and business problems and identify breakthrough opportunities.
• This position performs sophisticated data analytics by designing, developing, and deploying quantitative models and other analytics tools.
• Working with a multi-disciplinary team of Data Engineers, Data Architects, BI Developer and operational SME's, the AI Engineer will work on complex business problems and provide actionable insights with the overarching goal of improving clinical and financial outcomes., * Develop predictive models and machine learning algorithms that clinicians and staff will use to improve patient care, healthcare operations and financial performance.
• Develop and deploy LLM based Agentic AI and automation solutions using RAG or fine-tuning foundation models.
• Develop and deploy LLM based Agentic AI and automation solutions using RAG or fine-tuning foundation models.
• Develop and deploy LLM based Agentic AI and automation solutions using RAG or fine-tuning foundation models.
• Conduct rigorous model evaluation, including performance testing and bias assessment, to ensure the ethical and reliable deployment of AI systems.
• Mentor and guide junior members of the team sharing expertise in AI/ML techniques, model development, and deployment best practices.
• Design and implement RESTful APIs to integrate ML models or GenAI solutions with other applications and systems within the organization.

• Eight (8) years of experience in Machine Learning or Artificial Intelligence tools and technologies.
• Five (5) years of experience in Python or R and SQL.
• Two (2) years of experience as a Full Stack Machine Learning Engineer or similar role.
• Experience working with unstructured data, NLP technologies, and big data.
• Experience working with open-source ML libraries or frameworks such as PyTorch, TensorFlow, Keras, or Numpy.
• Experience with foundation models, prompt engineering, fine-tuning, or RAG.
• Experience working with cloud technologies such as AWS, Azure, or GCP.

Required Education:

• Bachelor's Degree in Business, IT, Math, Data Analytics, Engineering, or related discipline.

Preferred Education:

• Master's Degree in Business, IT, Math, Data Analytics, Engineering, or related discipline.