Anthropic

Applied AI Architect, Beneficial Deployments (Life Sciences Community & Enablement)

Owns scientific enablement for Claude across life sciences, running programs, demos, and a scientist community while scaling training to internal teams.

The role

This role sits within the Beneficial Deployments group's life sciences effort, which brings Claude to nonprofits and mission-driven partners. The person decides how scientists adopt Claude Science and related tools, through hands-on sessions and reusable materials. They also prepare internal customer-facing staff to carry that enablement forward without needing to be present.

What you would do

  • Own the scientific enablement agenda end to end: choose initiatives, build materials, deliver them, and track whether research groups become daily users.
  • Lead scientist activation efforts such as LSVP and Claude for Researchers, covering goals, program design, and execution.
  • Create demos, notebooks, and guides that show how frontier models can advance a scientist's own work, and share them publicly on social platforms.
  • Develop training and self-serve playbooks so Applied AI and Customer Success staff can support scientists independently.
  • Establish and steward a community of scientists using Claude, serving as its public face and supporting ambassador efforts at events of varying size.
  • Represent scientists' perspectives inside the company, turning their feedback into concrete requests and driving them to launch alongside marketing and communications.

What they asked for

  • Practical familiarity with AI science tools such as Claude Science, including where they excel and where they fall short.
  • Credible scientific background from academic labs, biotech, pharma, or research institutes, ideally using such tools yourself.
  • Track record of driving tool adoption across many research teams through demos, training sessions, workshops, or hackathons.
  • Current understanding of AI-for-science developments, including agentic analysis and AI co-scientist systems, and the ability to explain them to working scientists.
  • Hands-on experience with LLM APIs sufficient to prototype a working demo; production-grade engineering is not required.
  • Clear written and verbal communication for talks, tutorials, and documentation that scientists find genuinely useful.
  • History of carrying initiatives from concept to measurable results, setting direction and owning outcomes, often without an existing playbook.
  • Comfort working through ambiguity, structuring unclear problems, and taking on varied duties.
  • Bachelor's degree or equivalent experience in a relevant field.

Nice to have

  • Background designing or managing initiatives aimed at research audiences.
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