Clinical AI Architect

Healthcare client is seeking a Clinical AI Architect to design, implement, and optimize AI‑driven clinical solutions across care management, utilization management, and disease management workflows.

This role blends deep healthcare domain expertise with modern AI/ML capabilities to transform clinical decision support, improve patient outcomes, and streamline operational efficiency.

• Architect end‑to‑end Clinical AI solutions supporting care management, utilization management, and disease management programs.
• Lead design and integration of AI models into EMR/EHR ecosystems
  , including Epic and other major platforms.
• Develop clinical data pipelines leveraging structured and unstructured data from EMR/EHR, claims, HEDIS, SDOH, and care management systems.
• Partner with clinicians, nurses, care coordinators, and product teams to translate clinical workflows into scalable AI/automation solutions.
• Build frameworks for predictive analytics
  , risk stratification, disease progression modeling, and care‑gap identification.
• Ensure AI solutions comply with HIPAA
  , clinical safety, auditability, and explainability standards.
• Provide architectural guidance on interoperability standards such as FHIR, HL7, CCD, CCDA
  , and payer–provider data exchange.

• 8–12+ years in healthcare technology with at least 3–5 years in AI/ML architecture or clinical data engineering.
• Strong hands‑on experience with EMR/EHR systems — Epic preferred;
  Cerner, Allscripts, or similar acceptable.
• Deep understanding of Care Management, Utilization Management, and Disease Management workflows.
• Experience designing AI solutions for clinical decision support, triage, risk scoring, or care‑gap closure.
• Expertise with healthcare datasets:
  claims, clinical notes, lab results, ADT feeds, SDOH, and care plans.
• Strong knowledge of FHIR/HL7
  , clinical ontologies (LOINC, SNOMED, ICD‑10), and interoperability frameworks.
• Ability to work with data science teams on model development (NLP, GenAI, predictive modeling).
• Experience with cloud platforms (Azure/AWS/GCP) and modern data architectures.
• Excellent communication skills to interface with clinical, business, and technical stakeholders.

• Prior work with Community Care or Altruista (Guiding Care) platforms.
• Experience with care management systems, member engagement platforms, or population health tools.
• Background in building GenAI‑powered clinical assistants, summarization tools, or NLP pipelines.

• Bachelor’s or master’s in computer science, Health Informatics, Biomedical Engineering, or related field.