Senior AI Engineer - IT Innovation
Role details
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Tech stack
Requirements
Minimum Qualifications: Bachelor's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Information Systems, Health Care Informatics, or related field; or equivalent combination of education, training, certification, and/or related work experience. Five (5) years progressive professional experience in software engineering, data engineering, or machine learning engineering, enterprise application development, technical architecture, or comparable technical field. Three (3) years of hands-on experience designing, developing, integrating, or operating AI/ML solutions, including foundation model integration, custom AI workflows, model evaluation, production monitoring, and leading technical projects through requirements gathering, development, testing, deployment, and ongoing operational support. Five (5) years of progressively responsible experience across software engineering, data engineering, machine learning engineering, enterprise application development, technical architecture, or comparable technical domains.
Preferred Qualifications: Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, Health Informatics or related field. Training or certification in AWS, AWS Bedrock, or comparable cloud-based AI services, and in UiPath or similar robotic process automation or workflow automation platforms. Direct experience integrating with Epic electronic medical record system and Epic interoperability technologies, including HL7, FHIR, and SMART on FHIR. Experience working within a health care provider organization, preferably a multi-hospital system or integrated delivery network. Experience developing AI, automation, or analytics solutions that leverage enterprise data warehouses, data lakes/lake houses, curated data sets, vector stores, or embedding stores. Experience working with on-premises GPU/AI servers, local model hosting, open-source AI tools, model serving frameworks, and secure handling of localized data. Experience implementing AI-enabled robotic process automation and integrating RPA platforms with APIs, AI models, and workflow logic. Experience building and maintaining production-grade generative agents and secure APIs/integrations with enterprise systems. Experience integrating third-party AI applications, performing technical due diligence, coordinating vendor interfaces, and validating security, interoperability, supportability, and measurable value. Experience mentoring engineers, developers, analysts, or project team members, or serving as a technical lead for cross-functional delivery teams. Hands-on experience with cloud-based AI frameworks or managed foundation model services such as AWS Bedrock, Amazon SageMaker, or comparable enterprise AI platforms.