Applied AI Engineer, Beneficial Deployments, Life Sciences (Molecular Design)

About Anthropic

About Beneficial Deployments

Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most.

About the Role

We're looking for an Applied AI Engineer to join our Beneficial Deployments, Life Sciences team, focused on using Claude to speed up protein and small-molecule design. You'll work with research partners to apply modern design and structure models to real discovery problems, and build the agents and skills that turn those tools into end-to-end workflows. This role is about applying design models, not building new ones.

Responsibilities

• Work with research partners on protein and molecular design end-to-end with Claude, from advising, to prototyping, to writing production code.
• Work in a design–make–test loop with wet-lab partners (e.g. antibody-repertoire mining, MD prep / trajectory analysis at proteome scale) and turn the expert steps into reusable agents/skills.
• Build agents and skills that wrap design and structure tools into end-to-end workflows.
• Support research efforts aimed at better understanding the protein sequence-to-function relationship
• Help partners measure where AI speeds up their design cycles, and where it doesn't.
• Drive product, engineering and research direction from field experience, e.g. benchmarks and evals for design and structure tasks (capabilities and safety).
• Scale your impact to the long tail of labs through reusable skills, cookbooks and docs.
• Be an ambassador for Claude in molecular design, from small settings to large conferences.

You Might Be a Good Fit If You Have

• Hands-on experience applying protein or small-molecule design to real drug development programs, in an AI-first biotech, pharma, a rare-disease non-profit, a research institute, or a translational academic design lab.
• Experience with molecular dynamics (system prep, trajectory analysis) or large-scale antibody/immune-repertoire data, and with closing the loop against experimental results from a partner lab.
• Hands-on use of modern design and structure tools (e.g. AlphaFold, RFdiffusion, ProteinMPNN, Rosetta) to solve design problems, not only to build new models.
• Strong engineering skills: you can take an LLM-powered tool from prototype to production code, and write evals to measure its performance.
• Deep understanding on how to quantitatively measure success in drug design, experimentally and computationally.
• A scientist's instinct for understanding how AI can, and cannot, facilitate protein research and design
• Experience working directly with external customers or partners in a technical role.
• Clear written and verbal communication: docs partners can use without you, and talks that earn researchers' trust.
• A scrappy mentality: comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission.

Annual Salary

$280,000 — $320,000 USD