AI Practitioner- PRN
Summary:
The AI Practitioner serves as a flexible, project-based contributor within the Rogers Research Center, leading the design, development, implementation, and evaluation of advanced artificial intelligence solutions that support clinical care delivery, operational excellence, and behavioral health innovation.
This role is intended for an experienced AI professional with expertise in machine learning, large language models (LLMs), generative AI, natural language processing (NLP), and healthcare-focused AI deployment. The practitioner will support project-based strategic initiatives including grant-funded programs, pilot implementations, translational research efforts, and enterprise innovation projects.
The ideal candidate combines strong technical AI engineering capabilities with healthcare domain awareness, experience working with sensitive and complex clinical data, and the ability to rapidly prototype and operationalize scalable AI-enabled solutions within a highly regulated healthcare environment.
Job Duties & Responsibilities:
Lead discrete AI projects with clearly defined deliverables, timelines, and operational outcomes across clinical, research, and administrative domains
Design, prototype, and iterate AI-enabled solutions that improve patient care access, operational efficiency, clinical decision support, and workforce effectiveness
Develop proof-of-concept and production-ready applications utilizing machine learning, generative AI, LLMs, NLP, computer vision, and predictive analytics technologies
Evaluate emerging AI technologies, vendors, and frameworks to identify strategic applications within behavioral health and healthcare operations
Develop AI pipelines leveraging structured and unstructured healthcare data including EHR data, operational metrics, outcomes datasets, claims information, clinical notes, patient-reported outcomes, and multimodal research data
Build and optimize retrieval-augmented generation (RAG) architectures, prompt engineering frameworks, vector databases, and agentic AI workflows
Support model deployment, orchestration, monitoring, and lifecycle management in secure healthcare environments which may include the following:
Develop APIs, integrations, dashboards, and user-facing applications that operationalize AI outputs into clinical and business workflows
Monitor model performance, bias, drift, explainability, and reliability to ensure safe and effective deployment in real-world settings
Apply best practices in MLOps, version control, reproducibility, testing, and AI governance
Ensure AI systems are designed with scalability, interoperability, cybersecurity, and HIPAA compliance in mind
Design evaluation frameworks to assess the effectiveness, safety, usability, and operational impact of AI-enabled interventions
Support responsible AI practices through attention to ethical considerations, fairness, transparency, explainability, and human oversight
Ensure compliance with institutional data protection standards where applicable, including research procedures, HIPAA requirements, cybersecurity policies, and data governance frameworks
Additional Job Description:
Education/Training Requirements:
Minimum Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Biomedical Informatics, Engineering, Healthcare Analytics, or related field preferred
Experience developing and deploying AI/ML solutions within healthcare, behavioral health, hospital systems, digital health, or regulated industries
Demonstrated expertise with LLMs, generative AI systems, NLP, predictive modeling, and AI application development
Utilize modern AI development frameworks and tooling such as Python, PyTorch, TensorFlow, Hugging Face, LangChain, Azure AI, Microsoft Fabric, OpenAI APIs, and cloud-native AI infrastructure
Experience working with EHR platforms, healthcare interoperability standards, and clinical datasets preferred
Strong proficiency in Python and modern AI/ML frameworks and cloud platforms
Familiarity with healthcare privacy regulations, HIPAA compliance, and responsible AI governance practices
Experience supporting research initiatives, grants, publications, or IRB-governed projects preferred
Strong communication skills with the ability to bridge technical and operational audiences
With a career at Rogers, you can look forward to a Total Rewards package of benefits, including:
Health, dental, and vision insurance coverage for you and your family
401(k) retirement plan
Employee share program
Life/disability insurance
Flex spending accounts
Tuition reimbursement
Health and wellness program
Employee assistance program (EAP)
Through UnitedHealthcare, UMR and HealthSCOPE Benefits creates and publishes the Machine-Readable Files on behalf of Rogers Behavioral Health. To link to the Machine-Readable Files, please visit Transparency in Coverage (uhc.com)
The AI Practitioner serves as a flexible, project-based contributor within the Rogers Research Center, leading the design, development, implementation, and evaluation of advanced artificial intelligence solutions that support clinical care delivery, operational excellence, and behavioral health innovation.
This role is intended for an experienced AI professional with expertise in machine learning, large language models (LLMs), generative AI, natural language processing (NLP), and healthcare-focused AI deployment. The practitioner will support project-based strategic initiatives including grant-funded programs, pilot implementations, translational research efforts, and enterprise innovation projects.
The ideal candidate combines strong technical AI engineering capabilities with healthcare domain awareness, experience working with sensitive and complex clinical data, and the ability to rapidly prototype and operationalize scalable AI-enabled solutions within a highly regulated healthcare environment.
Job Duties & Responsibilities:
Lead discrete AI projects with clearly defined deliverables, timelines, and operational outcomes across clinical, research, and administrative domains
Design, prototype, and iterate AI-enabled solutions that improve patient care access, operational efficiency, clinical decision support, and workforce effectiveness
Develop proof-of-concept and production-ready applications utilizing machine learning, generative AI, LLMs, NLP, computer vision, and predictive analytics technologies
Evaluate emerging AI technologies, vendors, and frameworks to identify strategic applications within behavioral health and healthcare operations
Develop AI pipelines leveraging structured and unstructured healthcare data including EHR data, operational metrics, outcomes datasets, claims information, clinical notes, patient-reported outcomes, and multimodal research data
Build and optimize retrieval-augmented generation (RAG) architectures, prompt engineering frameworks, vector databases, and agentic AI workflows
Support model deployment, orchestration, monitoring, and lifecycle management in secure healthcare environments which may include the following:
Develop APIs, integrations, dashboards, and user-facing applications that operationalize AI outputs into clinical and business workflows
Monitor model performance, bias, drift, explainability, and reliability to ensure safe and effective deployment in real-world settings
Apply best practices in MLOps, version control, reproducibility, testing, and AI governance
Ensure AI systems are designed with scalability, interoperability, cybersecurity, and HIPAA compliance in mind
Design evaluation frameworks to assess the effectiveness, safety, usability, and operational impact of AI-enabled interventions
Support responsible AI practices through attention to ethical considerations, fairness, transparency, explainability, and human oversight
Ensure compliance with institutional data protection standards where applicable, including research procedures, HIPAA requirements, cybersecurity policies, and data governance frameworks
Additional Job Description:
Education/Training Requirements:
Minimum Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Biomedical Informatics, Engineering, Healthcare Analytics, or related field preferred
Experience developing and deploying AI/ML solutions within healthcare, behavioral health, hospital systems, digital health, or regulated industries
Demonstrated expertise with LLMs, generative AI systems, NLP, predictive modeling, and AI application development
Utilize modern AI development frameworks and tooling such as Python, PyTorch, TensorFlow, Hugging Face, LangChain, Azure AI, Microsoft Fabric, OpenAI APIs, and cloud-native AI infrastructure
Experience working with EHR platforms, healthcare interoperability standards, and clinical datasets preferred
Strong proficiency in Python and modern AI/ML frameworks and cloud platforms
Familiarity with healthcare privacy regulations, HIPAA compliance, and responsible AI governance practices
Experience supporting research initiatives, grants, publications, or IRB-governed projects preferred
Strong communication skills with the ability to bridge technical and operational audiences
With a career at Rogers, you can look forward to a Total Rewards package of benefits, including:
Health, dental, and vision insurance coverage for you and your family
401(k) retirement plan
Employee share program
Life/disability insurance
Flex spending accounts
Tuition reimbursement
Health and wellness program
Employee assistance program (EAP)
Through UnitedHealthcare, UMR and HealthSCOPE Benefits creates and publishes the Machine-Readable Files on behalf of Rogers Behavioral Health. To link to the Machine-Readable Files, please visit Transparency in Coverage (uhc.com)