About this role
JOB TITLE: Senior Engineer
REPORTING TO: Chief Technology Officer
DEPARTMENT: Digital Health
CLASSIFICATION LEVEL: Manager, Associate Director
LOCATION: Lusaka, Zambia
ABOUT HEALTHY LEARNERS
Healthy Learners is an award-winning non-profit organisation working to improve the health and learning of children across Zambia—and soon, beyond. In partnership with the Government of Zambia, we bring healthcare directly into schools so that children stay healthy, stay in class, and reach their full potential. Our model is government-owned and government-led, fully embedded in national priorities, systems, and structures.
Today, we have 1,062 health rooms, trained 8,370 School Health Teachers, and operate in 𝟰𝟱 districts across all ten provinces, reaching more than 1.4 million learners through Zambia’s first integrated School Health Program. Our approach combines school-based service delivery with technical assistance to government at every level—strengthening planning, supervision, data use, and local capacity to deliver.
As we complete our national scale-up, we’re focused on deepening programme quality, strengthening delivery systems, and laying the foundation for long-term government leadership. We’re looking for a dynamic operational leader to help drive this next chapter—someone ready to manage complexity at scale and help a proven model achieve lasting impact.
Healthy Learners is the proud recipient of the Skoll Award for Social Innovation, the Duke F.M. Kirby Prize, and the Lipman Family Prize from the University of Pennsylvania. These awards reflect not just our success to date, but the strength of the opportunity ahead. If this mission resonates with you, we’d love to hear from you.
ABOUT YOU
You exemplify the qualities of being Humble, Hungry, and Smart in your leadership:
• Humble (Continuous Learning & Inclusion): You actively seek, encourage, and facilitate feedback sharing, fostering an environment of continuous learning. You adapt and grow continuously, cultivating a culture of inclusion and belonging.
• Hungry (Efficiency, Excellence, and Innovation): Your relentless drive for efficiency and excellence is evident in your approach to both everyday tasks and complex challenges. When obstacles arise, you don't merely seek answers; you develop solutions and establish structures to address future obstacles proactively. Your hunger for innovation permeates the organisation, where you eagerly explore new and best practices, ensuring our people's operations remain modern and highly effective.
• Smart (Emotional Intelligence & Psychological Safety): Your exceptional emotional intelligence is your superpower, allowing you to create psychological safety within the organization. Through your ability to build trust, encourage risk-taking, and nurture courageous conversations, you promote an environment where individuals can thrive and collaborate effectively.
POSITION OVERVIEW
Healthy Learners is seeking a Senior Engineer to lead the design, development, quality assurance, deployment, and ongoing management of machine learning, health data, and digital health application systems. The role combines senior AI/ML engineering with data engineering, health informatics, data architecture, and systems integration. The successful candidate will gather user requirements, design data structures and pipelines, manage model performance, oversee third-party data contribution tools, and coordinate data integration planning with the Ministries of Health and Education.
The role requires particular competence in managing pediatric clinical data, including child health screening, referrals, treatment, follow-up, health outcomes, consent, privacy, and safeguarding considerations.This role involves minimal direct interaction with children and is classified as a low-contact position under the organisation’s Child Safeguarding Policy.
KEY RESPONSIBILITIES
• AI/ML and Model Management:
• Design, develop, test, deploy, and maintain machine learning models and AI-enabled systems supporting Healthy Learners’ health and program objectives.
• Establish model evaluation frameworks, quality assurance processes, performance metrics, and acceptance criteria.
• Conduct model QA, including output validation, accuracy assessment, error analysis, bias testing, edge-case testing, and data-quality checks.
• Monitor model performance, data drift, model drift, degradation, and potential safety risks.
• Manage model versioning, retraining, documentation, release processes, and rollback procedures.
• Ensure health-related models are appropriately validated, explainable, documented, and subject to human review.
• Evaluate model performance across relevant pediatric and underserved population groups.
• Model and Health Application Management:
• Apply appropriate privacy, pseudonymization, encryption, access control, audit, retention, and deletion practices for child health data.
• Ensure models are usable in Zambia’s operating context, including mobile-first use, intermittent connectivity, offline data capture, device limitations, and varying levels of digital literacy.
• Implement and evaluate model explainability and interpretability techniques to understand feature importance, prediction drivers, confidence, and model limitations, and to support appropriate human review of AI-assisted decisions.
• Feature and Data Engineering:
• Adapt existing or pretrained models to Healthy Learners' context through techniques such as fine-tuning, transfer learning, feature engineering, or domain-specific training.
• Evaluate when AI/ML deployment
• Prototype and evaluate models appropriate to local health and operational use cases, including computer vision, predictive analytics, classification, natural language processing, anomaly detection, and other relevant AI techniques.
• Design and maintain scalable data architectures, data models, data-flow diagrams, and reliable data pipelines.
• Perform routine ML data preparation and feature engineering tasks, including data ingestion, transformation, cleansing, validation, feature extraction, feature selection, feature engineering, annotation, normalization, dimensionality reduction, and training/validation dataset management.
• Support analytical datasets, dashboards, reporting systems, AI/ML workflows, and operational data products.
• Establish and review data standards, naming conventions, metadata requirements, data governance practices, and data-quality controls.
• Government and Third-Party Integration:
• Support data integration planning and technical coordination with the Ministries of Health and Education and other relevant stakeholders.
• Assess existing systems, reporting structures, workflows, data sources, interoperability requirements, and data ownership.
• Support secure integrations using APIs, databases, approved file exchange, mobile platforms, or other authorized mechanisms.
• Support configuration, and integration of third-party data contribution tools, mobile applications, APIs, and external data sources.
• Contribute technical input to data-sharing agreements, system documentation, and governance processes.
• Collaboration and Technical Leadership:
• Work closely with clinical, program, monitoring and evaluation, product, engineering, and operations teams.
• Lead testing, user acceptance testing, production releases, incident resolution, and continuous improvement.
• Mentor junior staff and promote best practices in AI/ML, data engineering, documentation, security, and testing.
• Communicate technical and health data concepts clearly to technical and non-technical audiences.
SKILLS & QUALIFICATIONS
• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Health Informatics, Public Health Informatics, Statistics, or a related field.
• 5–8 years of experience in ML engineering, data engineering, software engineering, health informatics, or digital health.
• Proven experience deploying and monitoring production ML models and managing model QA and performance.
• Strong experience with data pipelines, data architecture, APIs, databases, and system integration.
• Experience gathering user requirements and translating clinical or operational workflows into technical specifications.
• Strong Python and SQL skills, with experience using relevant ML and data tools.
• Understanding of child safeguarding, health data privacy, consent, information security, and responsible AI.
• Experience deploying AI/ML models on mobile devices, edge devices, embedded environments, or other resource-constrained platforms.
• Experience with Ministries of Health or Education, government systems, schools, health facilities, community health workers, or NGO programs.
• Familiarity with health information systems, digital health platforms, interoperability standards, mobile or offline-first applications, and referral-tracking systems.
• Experience with cloud platforms and MLOps practices.
• Strong understanding of responsible AI principles or frameworks (e.g., NIST AI Risk Management Framework or ISO/IEC 42001) is highly desirable.
• Must be a fully registered member of the Information and Communications Technology Association of Zambia (ICTAZ) with a valid practicing license.