Partner Manager, Global Health

Anthropics mission is to create reliable interpretable and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers engineers policy experts and business leaders working together to build beneficial AI systems.

Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits governments and mission-driven organizations to deploy Claude in education global health economic mobility and life sciences.

Were looking for a Partnerships Manager to drive forward the clinical AI research agenda for Anthropics global health work informing the tools that bring Claude safely into care and generating the evidence that proves they work.

Youll help define how clinical AI tools should be validated for use in low- and middle-income countries (LMICs) and youll help shape the tools and safeguards that make Claude safe and usable in clinical settings. This is a hands-on role as much as a research one: youll work side by side with Anthropics research evals and product teams translating what you know from how care actually gets delivered in low-resource settings into evaluations safeguards and product improvements.

Youll join a small tight-knit global health team within Beneficial Deployments. While youll lead on this domain you should expect to roll up your sleeves on adjacent workstreams help shape overall team strategy and be a thought partner to colleagues working on other parts of the health system. Everyone on the team owns the whole mission not just their lane.

• Own the clinical research and evaluation agenda for our global health work define what we need to prove to what standard and with whom and drive it.

• Design clinical evaluations and validation frameworks for LLMs in LMIC contexts covering accuracy safety multilingual performance and real-world conditions in close partnership with Anthropics research evals and product teams.

• Develop theories of change and outcome metrics connecting model capability to care quality health-worker performance and patient outcomes.

• Build and manage our global research partnerships and engage with relevant regulatory and normative bodies (WHO national authorities research-ethics bodies).

• Partner with internal research and product teams to improve Claude for clinical use cases in low-resource settings. Stay grounded in how care is actually delivered in LMICs so our tools and evaluations reflect those realities.

• Contribute across the broader global health portfolio lean in on adjacent workstreams help set strategy and be a thought partner to the team.

• Medical training and clinical practice (MD GP MBBS DO or equivalent) with direct experience delivering care in low-resource settings you reason fluidly from how diagnosis triage treatment and referral actually happen at the point of care in low and middle income countries.

• A concrete on-the-ground understanding of clinical and care-delivery workflows in LMICs and what they mean for how AI tools must be designed and evaluated.

• Direct experience evaluating or validating clinical AI/ML tools you understand 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 what counts as credible evidence for clinical safety and effectiveness.

• A strong command of the regulatory and normative landscape for clinical AI including WHO processes national regulatory authorities in LMICs and research ethics.

• A track record of building research partnerships with academic and in-country researchers treating local partners as scientific collaborators rather than data-collection sites.

• High agency a strong team orientation and comfort with ambiguity you pitch in outside your lane and thrive building the plane while flying it.

• A genuine drive to maximize impact for underserved communities and willingness to travel regularly to research and partner sites (25%).

• Hands-on experience building or shaping AI/ML products or tooling eval harnesses agentic scaffolding grounding and guardrails or clinical decision-support workflows.

• A publication record in digital health clinical AI evaluation or implementation science.

• Experience at a healthtech or AI company in clinical validation clinical quality or medical affairs.

• Experience working with philanthropic funders on evidence generation or research strategy.

• Direct clinical experience in a low- or middle-income country including with humanitarian or global-health delivery organizations.

Minimum education: Bachelors degree or an equivalent combination of education training and/or experience

Required field of study:A field relevant to the role as demonstrated through coursework training or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently we expect all staff to be in one of our offices at least 25% of the time. However some roles may require more time in our offices.

Visa sponsorship:We do sponsor visas! However we arent able to successfully sponsor visas for every role and every candidate. But if we make you an offer we will make every reasonable effort to get you a visa and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy so we urge you not to exclude yourself prematurely and to submit an application if youre interested in this work. We think AI systems like the ones were building have enormous social and ethical implications. We think this makes representation even more important and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams remember that Anthropic recruiters only contact you some cases we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money fees or banking information before your first day. If youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact advancing our long-term goals of steerable trustworthy AI rather than work on smaller and more specific puzzles. We view AI research as an empirical science which has as much in common with physics and biology as with traditional efforts in computer science. Were an extremely collaborative group and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic including: GPT-3 Circuit-Based Interpretability Multimodal Neurons Scaling Laws AI & Compute Concrete Problems in AI Safety and Learning from Human Preferences.

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits optional equity donation matching generous vacation and parental leave flexible working hours and a lovely office space in which to collaborate with colleagues. Guidance on Candidates AI Usage:Learn aboutour policy for using AI in our application process.