Partner Manager, Global Health
San Francisco, CA | New York City, NY
Posted 16d ago
About the job
Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The Beneficial Deployments team ensures AI reaches and benefits communities in need by partnering with nonprofits, governments, and mission-driven organizations. This role will drive the clinical AI research agenda for Anthropic's global health work, informing tools and generating evidence for their effectiveness. You will define how clinical AI tools are validated for low- and middle-income countries (LMICs) and shape tools and safeguards for Claude's safe and usable clinical application. This is a hands-on role requiring close collaboration with research, evals, and product teams to translate real-world care delivery knowledge into evaluations, safeguards, and product improvements.
Responsibilities
- Own the clinical research and evaluation agenda for global health work, defining proof requirements, standards, and partnerships.
- Design clinical evaluations and validation frameworks for LLMs in LMIC contexts, covering accuracy, safety, multilingual performance, and real-world conditions.
- Develop theories of change and outcome metrics linking model capability to care quality, health-worker performance, and patient outcomes.
- Build and manage global research partnerships and engage with regulatory and normative bodies.
- Partner with internal teams to improve Claude for clinical use cases in low-resource settings, ensuring tools and evaluations reflect real-world care delivery.
- Contribute to the broader global health portfolio, assisting with strategy and acting as a thought partner.
Requirements
- Medical training and clinical practice (MD, GP, MBBS, DO, or equivalent) with direct experience delivering care in low-resource settings.
- On-the-ground understanding of clinical and care-delivery workflows in LMICs and their implications for AI tool design and evaluation.
- Direct experience evaluating or validating clinical AI/ML tools, understanding the gap between benchmark performance and real-world clinical safety.
- Deep expertise in clinical research and evidence generation for digital health or AI tools, with a clear view of credible evidence for clinical safety and effectiveness.
- Strong command of the regulatory and normative landscape for clinical AI, including WHO processes, national regulatory authorities in LMICs, and research ethics.
- Track record of building research partnerships with academic and in-country researchers.
- High agency, strong team orientation, and comfort with ambiguity.
- Genuine drive to maximize impact for underserved communities.
- Willingness to travel regularly to research and partner sites (~25%).