Partner Manager, Global Health

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 Anthropic's 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.

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Minimum education: Bachelor’s 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 aren't 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 you're interested in this work. We think AI systems like the ones we're 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 from @anthropic.com email addresses. In 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 you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly 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. We're 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 about our policy for using AI in our application process.