Director of Engineering Clinical AI

Position Summary

We are seeking an innovative and experienced Director of Engineering Clinical AI to lead our initiatives in developing and implementing advanced AI solutions that enhance decision-making and operational efficiency within the clinical environment. The ideal candidate will possess a strong background in artificial intelligence, machine learning, and software engineering, with a focus on creating agentic systems that can operate autonomously while aligning with clinical objectives and improving patient outcomes.

This position offers the flexibility to work remotely from anywhere within the U.S.

• Leadership and Strategy: Develop and execute the strategic vision for clinical AI initiatives, ensuring alignment with organizational goals and clinical objectives. Drive the overall AI strategy and roadmap for clinical applications.
• Project Management: Oversee the planning, execution, and delivery of clinical AI projects, ensuring they are completed on time, within scope, and within budget. Establish best practices for project management across the clinical AI portfolio.
• Software Development: Lead the design and development of software solutions that incorporate clinical AI capabilities, ensuring they are robust, scalable, and maintainable. Champion the adoption of modern software development practices and tools tailored for clinical applications.
• Team Development: Build, mentor, and lead a high-performing team of AI engineers and software developers focused on clinical applications, fostering a culture of innovation, collaboration, and continuous improvement.
• Stakeholder Engagement: Collaborate with clinical leadership, healthcare professionals, and cross-functional teams to identify opportunities for AI integration in clinical workflows and gather requirements. Serve as the primary point of contact for clinical AI initiatives across the organization.
• Research and Development: Stay abreast of the latest advancements in clinical AI and machine learning technologies, evaluating their potential applications within the organization and integrating them into clinical software solutions. Promote a culture of research and innovation in clinical settings.
• Performance Monitoring: Establish metrics and KPIs to assess the effectiveness of clinical AI solutions, making data-driven decisions to optimize performance and drive continuous improvement in patient care.
• Compliance and Ethics: Ensure that all clinical AI initiatives adhere to ethical guidelines, regulatory requirements, and industry standards, promoting responsible AI usage within the clinical environment. Advocate for best practices in AI ethics and compliance in healthcare.

Minimum of [10] years of experience in AI/ML project management or a related role, with at least [6] years in a leadership position within the healthcare sector.

Proven track record of successfully managing clinical AI projects from conception to deployment at an organizational level.

• Strong understanding of AI/ML algorithms, frameworks, and tools (e.g., Tensor Flow, PyTorch, etc.) as they apply to clinical data.
• Proficiency in software development languages such as Python, Java, or C++.
• Extensive experience with software development methodologies and best practices, including version control and testing, specifically in clinical settings.

• Experience with project management methodologies (Agile, Scrum, etc.) at a strategic level.
• Strong organizational and multitasking abilities, with a focus on delivering results in a clinical context.

• Exceptional leadership and team management skills, with the ability to inspire and motivate a diverse team and drive organizational change in a clinical environment.

• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to clinical leadership and non-technical stakeholders.

• Experience with software development methodologies (e.g., Agile, Dev Ops).
• Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
• Knowledge of microservices architecture and containerization (e.g., Docker, Kubernetes).

• Familiarity with Electronic Health Records (EHR) systems and clinical workflows.
• Understanding of clinical terminologies and coding systems (e.g., SNOMED, LOINC, ICD
  10).
• Experience with clinical data analytics and reporting tools.

Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field;
Master's degree or PhD preferred, with a focus on healthcare or clinical applications.

The typical pay range for this role is:

$ - $

This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors…