Technical Advisor, Artificial Intelligence (AI) Engineer

The Technical Advisor, Artificial Intelligence (AI) Engineer will work with the Ministry of Health (MoH) National Health Intelligence Center (NHIC) in Rwanda to design, develop, and implement artificial intelligence (AI) solutions that strengthen the country's health system. The role involves transforming health data into actionable insights through model development, validation, and deployment. Responsibilities include building scalable AI architectures, developing algorithms, integrating predictive models into national digital health systems, and ensuring AI models are technically robust, clinically relevant, secure, interoperable, and ethically deployable. The incumbent will report to the NHIC/Health AI lead and the CHAI Digital Health program manager while collaborating with data scientists and digital health system teams. Key functions include AI model development and optimization, deployment and MLOps, system integration and interoperability, data management and security, model evaluation and regulatory support, documentation and reporting, collaboration and technical advisory, and continuous learning and innovation. The role is seconded to the National Health Intelligence Center (NHIC) and focuses on supporting Rwanda’s health system through AI-driven applications that improve decision-making and service delivery.

Master’s degree (or higher) in AI, Computer Engineering, Data Science, Biomedical Engineering, Health Informatics or a closely related field; minimum 6 years’ experience in applied machine learning, AI system development and production-grade deployments; strong experience in APIs and data pipelines; hands-on experience with full LLM stack (including model pretraining, fine-tuning, evaluation, and serving); advanced knowledge of reinforcement learning; proven experience deploying healthcare IT systems or medical AI agents in real-world environments; experience in designing and implementing scalable model evaluation frameworks; strong engineering capabilities for rapid iteration on data pipelines, training workflows, deployment, and maintenance; familiarity with explainable AI pipelines, version control, experiment tracking, and reproducible ML workflows; ability to integrate AI solutions with national digital health platforms using standards-based interoperability (e.g., APIs, HL7, FHIR); experience with data quality validation, bias detection, secure data handling, and compliance with national data governance and privacy laws.