AI Fellow - Africa Regional Offices

Note: This is a 12-month limited term employment position based in Abuja, Nigeria / Addis Ababa, Ethiopia / Johannesburg, South Africa / Nairobi, Kenya. Candidates must be able to legally work in the country where this position is located without visa sponsorship and relocation support will not be provided.

Sample project areas include

• Build decision-support tools across multiple African countries that unify disparate financing flow systems, conducts a periodic bottleneck diagnostics and supports informed decision-making.
• Design and prototype a solution to reduce stockouts of essential medicines at district and facility level, targeting countries facing drawdown of US Government-funded logistics management capacity.
• Strengthen health planning and supply chain systems by building an AI decision-support tool that ranks interventions against budget ceilings and traces prioritized interventions through procurement and cash release, developing a predictive analytics layer to forecast stock-out risk and flag redistribution opportunities before expiry

Your Role

The AI Fellows Program at the Gates Foundation is designed to accelerate the responsible and impactful use of AI in global health, development, and education. Our goal is to attract top-tier, mission-aligned AI talent to drive innovation in these areas. Building on the success of our US and India-based cohorts, we are expanding our program to Africa. As a Gates AI Fellow, you will join a prestigious cohort applying AI for public good and gain career-defining experience, access to Gates' powerful network, and exposure to senior leadership.

This role offers the unique opportunity to collaborate across multiple divisions within the Foundation—including Global Health (GH), Gender Equality (GE), Global Development (GD), and Global Growth & Opportunity (GGO)— to bridge the possibilities of frontier AI technology with the realities of deployment to create real, meaningful impact.

Over the course of 12 months, each AI Fellow will be assigned to high-priority projects, embedded within our Africa team. Fellows may contribute to multiple AI-oriented projects over the course of the fellowship, including concurrently, and should be comfortable adapting their technical approach as project needs evolve.

What You'll Do

Problem Identification & Scoping

Partner with the Africa team, other teams across the foundation and your specific project sponsors to scope potential AI solutions that can address real-world challenges, ensuring solutions are grounded in user needs and local realities and identifying the data, software, analytical, or operational components needed for those solutions to succeed.

Prototyping & Rapid Experimentation

• Prototype rapidly with modern large language models (LLM) and AI tools to test feasibility, generate insights, and create lightweight demos.
• Document findings from prototypes and translate them into actionable recommendations for scale or next steps.
• Identify linkages between your projects and others, building modularized solutions that can be reused across projects where appropriate.

Design and Deliver AI Solutions

• Design and prototype AI/Machine Learning (ML) models to address challenges in global health and development and integrate them into broader decision-support tools and workflows.
• Conduct rigorous model evaluation and validation, ensuring accuracy, fairness, and real-world applicability.
• Prepare, curate, integrate, and manage datasets and data pipelines, ensuring data integrity, provenance, security, and ethical use.
• Develop high-quality, reliable software, apply strong engineering practices such as clean code, version control, and robust testing.
• Leverage LLMs, including prompting, retrieval, tool use, deployment, and adaptation or fine-tuning where appropriate to specific use cases.

Teaching & Capacity Building

• Support internal AI literacy through, for instance, developing workshop sessions, guides, and playbooks to enable the Africa team to use LLM tools effectively in their own work.
• Mentor Africa team members in applying AI responsibly, with a focus on usability and adoption in Low- and Middle-Income Country (LMIC) contexts

Collaborate Across Teams and Partners

• Apply interdisciplinary problem-solving skills to translate AI research into practical solutions across multiple domains, combining AI with data engineering, analytics, optimization, or conventional software as needed.
• Communicate technical concepts effectively to both technical and non-technical partners, enabling shared understanding and informed decision-making.
• Collaborate with cross-functional teams across subject areas and geographies to co-design and deliver impactful solutions.
• Facilitate workshops and training sessions to demystify AI tools, enabling teams to directly apply solutions to their workflows.

Advance Responsible and Ethical AI

• Embed equity, bias mitigation, and data privacy in all technical approaches.
• Ensure prototypes are designed with explainability in mind, making them accessible to non-technical partners.
• Align AI solutions with the Foundation's mission and global health and development goals.
• Share thought leadership by integrating prior academic, research, or professional experiences to advance the responsible and impactful use of AI.

Your Experience

We are looking for fellows who represent a balance of technical competence and alignment with Foundation values.

• Education: Candidates must hold a bachelor's or master's degree (in Computer Science, Data Science, Engineering, Applied Math or relevant field).
• Experience: At least 2 years of experience applying AI solutions, preferably in health or agricultural systems.
• AI Technology: Strong foundation in modern AI/ML, including ML/AI modeling, model evaluation, and hands-on experience with LLMs, combined with software engineering and data skills needed to build end-to-end applied solutions. Evidence may come from applied coursework, research, internships, or early professional experience.

AI Applications: Demonstrated interest in applying AI to fields such as health systems, public financial management, supply chain and logistics, with enthusiasm and literacy to use modern AI tools safely and pragmatically (direct AI research experience not required). Candidates should be comfortable learning across adjacent technical areas - such as data engineering, time-series analysis, optimization, information retrieval, or decision-support systems - as project needs evolve.

• Collaborative Mindset: Strong teamwork and adaptability, with experience working cross-functionally in complex environments.
• Communication Skills: Demonstrated ability to clearly articulate technical concepts and recommendations to both technical and non-technical audiences.
• Mission-Driven Ethos: Deep motivation to apply AI responsibly for public good, with alignment to equitable development and global health impact.

Builder and Teacher Approach: Hands-on experience building prototypes with LLMs and other modern AI tools (e.g., using open-source tools or API-based platforms), with the judgment to connect AI components to the broader data and software systems needed for real-world use. Willingness to share findings openly and ability to teach and enable others, not just deliver technical outputs. leaders across AI, health, development, and policy while building a portfolio of real-world impact.