Genesis Healthcare System-posted 6 days ago
Full-time • Mid Level
1,001-5,000 employees

The AI Technical Architect will be a key member of our Data Services Team and will be a key influencer in the design and deployment of artificial intelligence and machine learning solutions across our healthcare system. This role, as an individual contributor, is responsible for translating business and clinical challenges into AI-driven opportunities, leveraging enterprise data (including Epic, Workday and Microsoft Fabric) to deliver predictive analytics, automation, and decision-support solutions. The AI Architect will partner closely with the Program Manager, Data Architects, Engineers, and clinical/business stakeholders to identify use cases, design scalable AI architectures, and operationalize models within secure and compliant environments. The AI Architect will focus on model design, deployment, and operationalization, while collaborating with Data Architects for data sourcing and pipeline integration. The ideal candidate combines deep knowledge of AI/ML frameworks and cloud-based AI services with the ability to guide leaders and end users through the adoption of advanced technologies that improve patient outcomes, operational efficiency, and workforce productivity.

  • Design and deploy scalable, secure AI/ML solutions for healthcare applications.
  • Translate business and clinical requirements into AI/ML architecture.
  • Leverage Microsoft Azure AI Services (Cognitive Services, Machine Learning Studio, Azure OpenAI) and related tools (Fabric, Data Factory, Synapse) to develop cloud-based solutions.
  • Integrate and analyze data from Epic (Clarity, Caboodle) and other clinical/operational sources.
  • Collaborate with Enterprise Data Architect to ensure high-quality and compliant data pipelines are aligned with interoperability standards (FHIR, HL7).
  • Develop and deploy models using Python, R, TensorFlow, PyTorch, Scikit-learn, or similar frameworks.
  • Implement CI/CD pipelines and MLOps workflows for model deployment, monitoring, and lifecycle management.
  • Ensure compliance with HIPAA, PHI, and responsible AI practices (explainability, bias mitigation, transparency).
  • Coordinate vendor engagement and contract management through a shared collaboration with the Enterprise Data Architect and/or AI Program Manager.
  • Individual Contributor (IC) on our Intelligent Automation Team working closely with the Program Manager or Project Managers on AI and automation projects from concept to production, applying Agile methodologies (Scrum, Kanban).
  • Define technical scope, objectives, milestones, and deliverables while working with your direct manager who will manage resources and dependencies across IT, clinical, and business teams.
  • Work with the Program Manager on iterative sprints for prototyping, validation, and production readiness; conduct demos, participate in retrospectives, and assist with sprint planning.
  • Identify technical project risks (e.g., adoption, data quality, compliance) and develop mitigation strategies.
  • Establish and maintain best practices for AI/ML development, change management, and operational documentation using a common repository, like ServiceNow knowledgebase, for documentation to insure transparency and accessibility. Collaboration with the Enterprise Data Architect to develop unified standards for documentation
  • Serve as the technical liaison between AI teams, business units, clinical leadership, IT, and external vendors.
  • Facilitate workshops, discovery sessions, and requirements gathering to align goals and priorities.
  • Translate complex AI/ML concepts into accessible language for non-technical stakeholders.
  • Foster collaboration and workflow adoption across clinical, operational, and technical teams.
  • Provide training, mentorship, and communication to increase AI literacy and user trust.
  • Document solution designs, governance frameworks, and lessons learned; communicate progress and outcomes in clear, actionable terms.
  • Work collaboratively with Epic resources, Application Build Teams and other resources to implement Epic’s offerings of AI/ML as a software feature.
  • Analyze clinical, operational, and business processes to identify AI opportunities and evaluate ROI.
  • Translate ambiguous requirements into clear technical specifications and validate complex datasets.
  • Diagnose workflow inefficiencies and perform root cause analysis to guide solution design.
  • Optimize algorithms, models, and processes for accuracy, efficiency, and clinical relevance.
  • Monitor deployed solutions for issues or drift and recommend improvements based on performance and feedback.
  • Provide analytical recommendations for leadership and assess risks associated with AI adoption.
  • Stay current with AI/ML frameworks, cloud services, and healthcare technology trends.
  • Collaborate with the Enterprise Data Architect and IT Leadership to develop a unified roadmap for technology evaluation and adoption, with joint sign-off.
  • Adapt to shifting priorities, evolving data landscapes, and unexpected challenges.
  • Participate in ongoing training and certifications; encourage team members to do the same.
  • Promote a culture of experimentation and innovation while managing risk responsibly.
  • Provide technical guidance and oversight for AI/ML solution design, deployment, and operationalization.
  • Mentor and coach team members to foster professional growth, continuous learning, and best practices adoption.
  • Lead cross-functional AI projects, ensuring alignment with organizational goals and clear prioritization.
  • Champion AI adoption across clinical and operational teams, influencing stakeholders toward data-driven approaches.
  • Establish and promote standards, guidelines, and reusable components for AI/ML projects.
  • Partner with leadership to define AI strategy and roadmap, fostering innovation, accountability, and ethical AI practices.
  • Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Information Technology, or a related field. An equivalent combination of education, certifications, and experience will be considered.
  • Six (6) years of experience in solution architecture, data science, or AI/ML engineering, preferably within healthcare or other regulated industries.
  • Proven experience designing and deploying AI/ML solutions using cloud platforms (Azure strongly preferred).
  • Experience working with clinical and operational data from Epic (Clarity, Caboodle) or similar healthcare systems.
  • Demonstrated success in operationalizing AI models into production environments with MLOps practices.
  • Experience collaborating with cross-functional teams (clinical, business, IT, and executive leadership) to identify and deliver AI use cases.
  • Vendor and technology evaluation experience, with a track record of guiding adoption of emerging AI tools.
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