CCL Global is seeking for an AI & Digital Health Product Manager – Smart Clinics & National Screening Programs

Position Overview

The AI & Digital Health Product Manager will lead the development, deployment, and optimization of AI‑enabled smart clinic solutions and national screening programs. This role sits at the intersection of healthcare, technology, and public health, driving digital transformation through intelligent reporting, automated diagnostics, and integrated patient pathways.

The ideal candidate combines strong product leadership with a deep understanding of clinical workflows, AI technologies, and large‑scale health system operations. They will work closely with clinicians, government stakeholders, data scientists, and technology partners to deliver impactful, scalable digital health solutions.

Key Responsibilities

Product Strategy & Roadmap

• Define and execute the product vision for AI‑powered smart clinic solutions and national screening platforms.
• Develop product roadmaps aligned with clinical needs, regulatory requirements, and national health priorities.
• Identify opportunities to enhance screening accuracy, workflow efficiency, and patient experience through AI and automation.

AI & Digital Health Solution Development

• Lead the design and implementation of AI‑driven reporting tools for radiology, pathology, ophthalmology, cardiology, and other screening domains.
• Collaborate with data science and engineering teams to validate AI models, ensure clinical relevance, and optimize performance.
• Oversee integration with EMRs, PACS, HIS, and national health information exchanges.
• Ensure solutions meet cybersecurity, privacy, and regulatory standards.

Smart Clinic Enablement

• Design digital workflows for smart clinics, including patient intake, triage, screening, AI‑assisted reporting, and follow‑up pathways.
• Work with clinical teams to streamline operations and embed AI tools into daily practice.
• Support deployment, onboarding, and continuous improvement across clinic sites.

Stakeholder Engagement & Program Management

• Engage with ministries of health, public health authorities, hospital leadership, and clinical experts.
• Lead cross‑functional coordination across technology partners, vendors, and implementation teams.
• Prepare business cases, impact reports, and strategic presentations for senior stakeholders.
• Monitor program KPIs, adoption metrics, and clinical outcomes.

User Experience & Training

• Conduct user research with clinicians, technicians, and administrative staff to refine product features.
• Develop training materials, workflows, and best‑practice guidelines for AI‑enabled screening.
• Ensure high user adoption and satisfaction through continuous support and feedback loops.

Compliance, Quality & Risk Management

• Ensure all AI tools and digital health solutions comply with medical device regulations, data protection laws, and ethical AI standards.
• Support clinical validation studies, pilots, and post‑market surveillance activities.
• Identify and mitigate risks related to AI accuracy, workflow integration, and patient safety.

Qualifications & Experience

• Bachelor’s or Master’s degree in Biomedical Engineering, Health Informatics, Computer Science, Public Health, or related field.
• 4–7 years of experience in digital health, AI healthcare products, health IT, or medical device product management.
• Strong understanding of clinical workflows, screening programs, and digital health ecosystems.
• Experience with AI/ML solutions in healthcare (e.g., radiology AI, predictive analytics, automated reporting).
• Familiarity with EMR/HIS/PACS integration, interoperability standards, and health data governance.
• Excellent communication, stakeholder management, and project leadership skills.
• Experience working with government health entities or national programs is a strong advantage.

Key Competencies

• Strategic thinking with the ability to translate clinical needs into digital solutions.
• Strong technical literacy in AI, data pipelines, and digital health architectures.
• Exceptional stakeholder engagement and cross‑functional leadership.
• Analytical mindset with a focus on outcomes, quality, and scalability.
• High professionalism, ethical judgment, and commitment to responsible AI.