The Clinton Health Access Initiative, Inc. (CHAI) is a global health organization committed to our mission of saving lives and reducing the burden of disease in low-and middle-income countries. We work at the invitation of governments to support them and the private sector to create and sustain high-quality health systems.

CHAI was founded in 2002 in response to the HIV/AIDS epidemic with the goal of dramatically reducing the price of life-saving drugs and increasing access to these medicines in the countries with the highest burden of the disease. Over the following two decades, CHAI has expanded its focus. Today, along with HIV, we work in conjunction with our partners to prevent and treat infectious diseases such as COVID-19, malaria, tuberculosis, and hepatitis. Our work has also expanded into cancer, diabetes, hypertension, and other non-communicable diseases, and we work to accelerate the rollout of lifesaving vaccines, reduce maternal and child mortality, combat chronic malnutrition, and increase access to assistive technology. We are investing in horizontal approaches to strengthen health systems through programs in human resources for health, digital health, and health financing. With each new and innovative program, our strategy is grounded in maximizing sustainable impact at scale, ensuring that governments lead the solutions, that programs are designed to scale nationally, and learnings are shared globally.

At CHAI, our people are our greatest asset, and none of this work would be possible without their talent, time, dedication and passion for our mission and values. We are a highly diverse team of enthusiastic individuals across 40 countries with a broad range of skillsets and life experiences. CHAI is deeply grounded in the countries we work in, with majority of our staff based in program countries. Learn more about our exciting work: http://www.clintonhealthaccess.org

CHAI is an Equal Opportunity Employer, and is committed to providing an environment of fairness, and mutual respect where all applicants have access to equal employment opportunities. CHAI values diversity and inclusion, and recognizes that our mission is best advanced by the leadership and contributions of people with diverse experience, backgrounds, and culture.

Position Overview:

The Government of Rwanda (GoR) strives to achieve Universal Health Coverage (UHC) by enabling equitable access to quality health services for the population as outlined in the Fifth Health Sector Strategic Plan (HSSP V). This commitment has been made against a backdrop of rising health care costs and uncertainty around the future availability of donor funding and calls for improved health sector sustainability. Acknowledging this, the Government aims to employ effective, equitable, efficient, and sustainable health care financing and systems strengthening, putting an emphasis on primary health care as the cornerstone of a strong and sustainable health system.

CHAI Rwanda’s Health System Strengthening (HSS) programs work on a day-to-day basis with Government leadership in the Ministry of Health (MoH) and the Rwanda Social Security Board (RSSB). The goal of those programs is to support the Government to accelerate progress towards UHC by ensuring the sustainable delivery of quality, essential health services. This includes work to design and implement national Primary Health Care (PHC) reforms from health center level down to community health, to increase health workforce availability, to prioritize and sustainably finance essential services, and to support improved management, financing, and delivery of quality primary health care.

CHAI currently seeks two skilled and innovative AI Engineers to work with the Ministry of Health (MoH) National Health Intelligence Center (NHIC) to support the design, development, and implementation of artificial intelligence (AI) solutions that strengthen Rwanda’s health system. The AI Engineers will play a key role in transforming health data into actionable insights through model development, validation, and deployment.

As an AI Engineer, you will contribute to building scalable AI architectures, develop algorithms, and integrate predictive models into national digital health systems. You will be responsible for the design, development, deployment, monitoring, and optimization of production-grade AI systems that address national public health and clinical priorities. This role ensures that AI models are technically robust, clinically relevant, secure, interoperable, and ethically deployable within Rwanda’s digital health ecosystem. The incumbents will be seconded to the National Health Intelligence Center (NHIC) and will report to the NHIC/Health AI lead and the CHAI Digital Health program manager while working collaboratively with the data scientists, and digital health system teams to translate public health priorities into AI-driven applications that support decision-making and improve service delivery.

The key functions and deliverables of this role will include:

1. AI Model Development and Optimization

• Design, develop, train and optimize machine learning and deep learning models to strengthen the health system with AI capabilities.
• Conduct data preprocessing, feature engineering, model training, validation, tuning and performance optimization.
• Develop explainable AI pipelines to support clinical trust and regulatory transparency.
• Apply best practices in version control, experiment tracking, and reproducible ML workflows.

2. Deployment, MLOps and post-deployment monitoring

• Deploy AI models into secure, scalable production environments.
• Establish and maintain model performance monitoring, data and concept drift detection, automated retaining pipelines, and incident and rollback mechanisms.
• Optimize model inference speed, system reliability, and compute cost efficiency.
• Maintain structured model versioning, release management, and retirement protocols.

3. System integration and interoperability

• Integrate AI solutions with national digital health platforms, including EMRs, HMIS, LMIS, and other MoH systems
• Implement standards-based interoperability using APIs, HL& FHIR, and MoH recommended architecture patterns
• Develop real-time and batch data pipelines that enable secure AI inference in live workflows

4. Data Management, Quality and Security

• Work with NHIC data teams to access, clean, label, and manage large structured and unstructured datasets.
• Enforce data quality validation, bias detection, and representativeness checks.
• Implement secure data handling, encryption, access controls, and audit logging in compliance with national data governance and privacy laws.
• Maintain full dataset documentation and lineage tracking.

5. Model Evaluation, Testing, Clinical Validation and Regulatory support

• Conduct rigorous testing of AI models to ensure accuracy, fairness, and clinical relevance.
• Support clinical pilots, facility-level validation, and workflow integration testing.
• Prepare technical documentation for ethics committees, regulatory reviews, and audit processes.
• Perform error analysis and continuous refinement based on real-world clinical feedback.

6. Documentation, Reporting, and Knowledge Sharing

• Produce clear documentation for model architecture, training processes, deployment pipelines and integration workflows
• Provide inputs to technical reports, donor updates, concept notes and system design briefs.
• Support the development of user guides, SOPs, and training materials for health workers and system administrators.

7. Collaboration and Technical advisory

• Work closely with the other team members and departments within the health sector to improve and scale AI infrastructure
• Engage in weekly AI review sprints, technical design sessions and AI TWGs.
• Provide AI engineering support to Grant proposals, research collaborations, and public-private partnerships.

8. Continuous Learning and Innovation

• Stay updated on advancements in AI and AI technology
• Explore emerging tools and frameworks for national-scale deployments of AI solutions.
• Proactively propose new high-impact use cases for the health sector.

Education

• Master’s degree (or higher) in AI, Computer Engineering, Data Science, Biomedical Engineering, Health Informatics or a closely related field.
• A minimum of 6 years’ experience in Applied Machine learning, AI system development and production-grade deployments

Technical Expertise

• Strong experience in APIs, data pipelines, training workflows, deployment, maintenance and ML frameworks and systems integration.
• Hands-on experience across the full LLM stack, including model pretraining, fine-tuning, evaluation, and serving.
• Demonstrated ability to design and implement scalable model evaluation frameworks, including model-based assessment techniques.
• Advanced knowledge of reinforcement learning, including algorithm design, environment interaction, and performance evaluation.
• Strong engineering capabilities for rapid iteration on data pipelines, training workflows, deployment, and maintenance.
• Proven experience deploying and sustaining healthcare IT systems or medical AI agents in real-world environments.

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