You will own the clinical research and evaluation agenda for OpenEvidence in global health. You will design the clinical evaluations and validation frameworks that establish how OpenEvidence performs in LMIC contexts, covering accuracy, safety, multilingual performance, and real-world conditions, working side by side with our research, evaluation, and product teams. You will develop theories of change and outcome metrics that connect OpenEvidence's capabilities to care quality, health-worker performance, and patient outcomes, and you will help shape the safeguards that make the product safe and usable at the point of care. You will stay grounded in how care is actually delivered in low-resource settings and translate that into product improvements, not just evaluations. You will join a small, tight-knit global health team: you lead on this domain, but you should expect to roll up your sleeves on adjacent workstreams, help set overall strategy, and be a thought partner to colleagues working on other parts of the health system. You will spend roughly 25% of your time at research and partner sites. Specific skillsets are secondary to the clinician-builder profile above, but some important spikes for different facets of this work are: Clinical AI evaluation - You have direct experience evaluating or validating clinical AI/ML tools, and you understand the gap between benchmark performance and real-world clinical safety. - You have deep expertise in clinical research and evidence generation for digital health or AI tools, with a clear view of what counts as credible evidence for safety and effectiveness. Evaluation and quantitative proof are first-class citizens to you. Regulatory and normative landscape - You have a strong command of the regulatory and normative landscape for clinical AI, including WHO processes, national regulatory authorities in LMICs, and research ethics. Research partnerships - You have a track record of building research partnerships with academic and in-country researchers, and you treat local partners as scientific collaborators rather than data-collection sites. - You may have worked with philanthropic funders on evidence generation or research strategy. Industry and field experience - You might have experience at a healthtech or AI company in clinical validation, clinical quality, or medical affairs, or a publication record in digital health, clinical AI evaluation, or implementation science. - You might have direct clinical experience in a low- or middle-income country, including with humanitarian or global-health delivery organizations. We work in person in Miami and SF, and this role travels regularly (~25%) to research and partner sites. We believe in creating an environment that optimizes for focus and productivity, including providing meals, transport, and anything else you need to move quickly.