Associate Director, Applied AI

Overview

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 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 skill sets and life experiences. CHAI is deeply grounded in the countries we work in, with the 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.

Program Overview

Leveraging deep expertise in strengthening healthcare systems, CHAI has launched an ambitious Artificial Intelligence (AI) initiative to support Ministries of Health to systematically capture and scale the benefits of AI. The CHAI AI program seeks to support Ministries to reimagine what is possible with technology, building towards a vision of “AI Native Health Systems” that makes health care delivery accessible, high-quality, and efficient. There are four pillars of the strategy: (1) bringing the capabilities of world-class clinical intelligence or “AI Doctors” to every clinician and patient, (2) developing and deploying new “AI Diagnostics” that decentralize and improve quality of diagnoses, and (3) health systems AI applications, or the creation of “National Health Intelligence Centers” that improve systems capacity in disease surveillance, financial and workforce management, supply chain, and beyond. Finally, (4) to fully realize the potential of these uses of AI, CHAI is also supporting Ministries of Health to strengthen “AI Foundations”, including physical and digital infrastructure, governance, and workforce strategy.

Position Overview

The Associate Director, Applied AI will serve as CHAI's senior technical expert in machine learning and AI, advising CHAI projects and Ministries of Health on best practices for the responsible deployment of ML and AI. The individual will bring depth across both traditional machine learning and data science—supervised learning, optimization, time series, and related methods—and hands-on experience with newer AI tools such as large language models and agentic systems. This combination allows the individual to guide teams toward the right technical approach for a given problem, rather than defaulting to any single method.

This is a senior role that begins with significant individual-contributor and senior-advisor work and grows over time into building and leading a global team of technical experts. The individual will support a broad and varied portfolio of projects, providing technical guidance to CHAI teams and government partners at every stage—from framing a problem and selecting an approach, through model development, to measuring and validating performance. A central and somewhat distinctive part of the role is quality assurance: ensuring that CHAI teams and external technical partners follow sound practices in model building, evaluation, and performance measurement.

The individual will work across program areas and country offices, acting as a trusted technical reviewer and advisor rather than the sole builder. As the portfolio grows, the individual will recruit, mentor, and lead a team of technical experts capable of supporting projects across CHAI's work. This role reports to the Senior Director, Head of AI and involves regular travel to CHAI program countries.

Responsibilities

• Serve as CHAI's senior technical advisor on machine learning and AI, guiding CHAI projects and Ministries of Health on best practices for responsible model development and deployment
• Advise teams on selecting appropriate technical approaches across both traditional machine learning and data science (e.g., supervised learning, optimization, time series) and newer AI tools (e.g., large language models, agentic systems)
• Provide quality assurance across a broad portfolio of projects, reviewing the work of CHAI teams and external technical partners to ensure sound practices in model building, evaluation, and performance measurement
• Establish and promote standards, methods, and guidance for rigorous model development and validation across the AI team's work
• Provide hands-on technical guidance and senior-advisor support to a wide range of projects at varying stages of maturity
• Recruit, mentor, and build a global team of technical experts to support projects across CHAI's work as the portfolio grows
• Partner with government counterparts to build their capacity to develop, evaluate, and sustain ML and AI solutions
• Translate technical concepts and trade-offs clearly for non-technical audiences, including senior government and program stakeholders
• Stay current with developments in machine learning and AI and assess their relevance and applicability to CHAI's work
• Undertake other responsibilities as needed to advance the technical quality of the AI team's work

Qualifications

• Passion for AI and its potential to improve health systems in low- and middle-income countries
• 8 to 12+ years of relevant professional experience in machine learning, data science, or a closely related technical field
• Deep expertise in traditional machine learning and data science methods, such as supervised learning, optimization and linear programming, and time series analysis
• Hands-on experience with newer AI tools and approaches, including large language models and agentic systems
• Demonstrated ability to evaluate model quality and rigorously measure and validate model performance
• Advanced degree in a quantitative or technical discipline such as data science, statistics, biostatistics, bioinformatics, computer science, or a related field, or equivalent practical experience
• Excellent communication skills, including the ability to explain technical concepts to non-technical audiences
• Ability to think strategically, handle ambiguity, and problem solve in a fast-paced, limited-structure, multicultural environment
• Willingness to undertake regular travel to CHAI program countries, including occasional multi-week periods

Preferred Qualifications

• Experience applying machine learning or AI in health, global health, or global development contexts
• Experience working in low- and middle-income country settings
• Experience working with governments or Ministries of Health
• Experience building, mentoring, or leading technical teams

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