Mid-Level AI Transformation Engineer; Remote

Overview

Mid-Level AI Transformation Engineer (Remote) at Ennoble Care, Hackensack, NJ. Ennoble Care provides mobile primary care, palliative care, and hospice services to patients across multiple states and aims to improve patient outcomes through AI-enabled solutions aligned with compassionate care.

We are seeking a Mid-Level AI Transformation Engineer to drive artificial intelligence innovation within our healthcare organization, bridging cutting-edge AI technology and compassionate care to transform operations and support elderly and hospice patients.

The ideal candidate will have a strong technical foundation in AI/ML, practical healthcare experience, and a passion for using technology to improve lives during critical stages of care. Please note that we cannot sponsor visa candidates at this time.

• AI Solution Development:
  Design, develop, and deploy AI-powered solutions tailored to senior care and hospice operations, including predictive analytics for patient deterioration, automated documentation systems, and intelligent care coordination tools.
• Healthcare Process Optimization:
  Analyze clinical and operational workflows to identify opportunities for AI integration that enhance efficiency while maintaining the human-centered approach essential to hospice and senior care.
• Data Strategy & Integration:
  Collaborate with IT and clinical teams to integrate AI solutions with existing EHR systems, ensuring HIPAA compliance and data security while maintaining accessibility for healthcare providers.
• Clinical Decision Support:
  Build and refine machine learning models that assist healthcare providers in early detection of complications, symptom management, and personalized care planning for elderly and end-of-life patients.
• Stakeholder
  
  Collaboration:
  
  Work with physicians, nurses, administrators, and family services teams to understand needs, gather requirements, and ensure AI solutions align with clinical best practices and organizational goals.
• Training & Change Management:
  Develop training materials and conduct workshops to help staff understand and effectively utilize AI tools, ensuring smooth adoption and value realization.
• Performance Monitoring:
  Establish KPIs and continuously monitor AI system performance, making iterative improvements based on feedback and outcomes data.
• Regulatory Compliance:
  Ensure all AI implementations comply with healthcare regulations including HIPAA, FDA guidelines for clinical decision support, and ethical AI principles in healthcare.
• Innovation Research:
  Stay current with emerging AI technologies, healthcare AI applications, and industry best practices, recommending opportunities for AI-driven improvements in senior and hospice care.

• Bachelor's degree in Computer Science, Data Science, Engineering, or related technical field
• 3-5 years of experience in AI/ML engineering, data science, or related technical roles
• Proven experience with machine learning frameworks (Tensor Flow, PyTorch, scikit-learn) and programming languages (Python, R, C#)
• Strong understanding of healthcare data standards (HL7, FHIR) and electronic health record systems
• Knowledge of HIPAA compliance, data privacy regulations, and healthcare security requirements
• Experience with cloud platforms (AWS, Azure, or GCP) and deploying ML models in production environments
• Excellent communication skills with ability to explain technical concepts to non-technical stakeholders
• Demonstrated ability to work collaboratively in cross-functional healthcare teams
• Strong problem-solving skills and ability to translate business requirements into technical solutions
• Commitment to ethical AI development and patient-centered care philosophy

• Master's degree in Computer Science, Artificial Intelligence, Biomedical Informatics, or related field
• Previous healthcare experience, particularly in geriatric care, palliative care, or hospice settings
• Experience with natural language processing (NLP) for clinical documentation and medical text analysis
• Familiarity with predictive analytics for patient risk stratification and outcome prediction
• Knowledge of telemedicine platforms and remote…