Ai Engineer

Ai Engineer 8700 Data Analytics and InsightsSchedule: Salaried. About the Position Build, integrate, and advance AI-powered solutions that improve how care is delivered, documented, and supported across the organization. You will work hands-on with engineers, clinical informatics leaders, and analytics partners across Epic, Microsoft Fabric, Azure AI Foundry and emerging agent-based platforms to bring practical, production-ready AI capabilities into real clinical and operational workflows Overview of Responsibilities Design, build, deploy, and support AI agents and agent-based solutions across Epic Agent Factory and Azure AI Foundry. Develop and implement AI-enabled solutions using Epic Cognitive Computing, clinical decision support, predictive models and workflow-embedded AI to enhance care delivery and clinical documentation. Develop Python-based AI solutions, integrate LLM APIs with Epic using REST APIs and HL7/FHIR, and design, evaluate, optimize, and deploy prompt flows in Azure AI Foundry. Build data pipelines and Lakehouse solutions in Microsoft Fabric and support the development of semantic models and reporting assets in Power BI. Leverage GitHub Copilot to accelerate development while maintaining high standards for code quality, documentation and supportability. Support Abridge ambient documentation workflows and monitor the performance of models and agents in production environments. Collaborate in agile delivery processes through sprint planning, iterative development and code reviews. Apply responsible AI practices consistent with HIPAA requirements and Reid Health’s AI governance framework. Education & Experience Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field. Hands-on experience building and deploying AI applications using LLM APIs such as OpenAI, Anthropic, or Hugging Face, including prompt engineering and agent-based development using frameworks such as LangChain, AutoGen, Microsoft Semantic Kernel, or similar tools. Proficiency with Azure AI Foundry, Microsoft Fabric, Power BI, including Power BI Copilot and GitHub Copilot. Strong technical skills in Python and SQL, with experience using libraries such as Pandas, scikit-learn and PyTorch. Solid understanding of NLP, transformers, embeddings, vector databases and retrieval-augmented generation (RAG) is expected. Experience designing, evaluating and optimizing AI workflows, including prompt flows, grounding strategies and production deployment. Experience integrating AI solutions into enterprise systems, ideally in healthcare environments using REST APIs and HL7/FHIR standards. Familiarity with model and agent monitoring, agile delivery practices, responsible AI principles and HIPAA-compliant handling of protected health information.