Software Engineer, Staff: Applied AI, Science & Engineering
Anthropic · New York City, NY; San Francisco, CA; Seattle, WA
About this role
## About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems—AI that is safe and beneficial for users and society. ## About the role Anthropic is building AI systems that can help tackle hard scientific and engineering problems. Claude can read literature, run simulations, analyze results, and iterate—but many real-world problems aren’t well-posed. This role focuses on bridging research breakthroughs with real-world applications by turning partner problems (with their data, tools, constraints, and experts) into work a model can actually do and verify. You’ll join the **Applied AI, Science & Engineering** team, where we build the software and systems that enable Claude to perform applied research and engineering work. This is an engineering-first role: you’ll prototype quickly with domain experts, then build and harden the systems to make the workflow repeatable. ## Responsibilities - Build agent harnesses and research loops to move from literature review → hypothesis generation → simulation → analysis → design iteration - Integrate scientific computing and simulation tools (e.g., finite element, CFD, electromagnetic, molecular modeling) so Claude can run them reliably and at scale - Design and build evaluations to determine whether Claude’s work is actually correct (and be clear about where it isn’t) - Work with scientists and engineers at partner organizations to understand problems, data, tools, and constraints—and convert open-ended questions into well-specified, verifiable tasks with clear success criteria - Prototype with partners, ship pilots into their workflows, and remove anything that doesn’t advance the problem - Turn what works into shared tools, reusable components, and documented processes - Serve as a technical voice on how Claude performs on science/engineering work—explaining results, limits, and tradeoffs clearly to both technical and non-technical stakeholders - Partner with research and product teams to share where models fall short and help shape what comes next ## You may be a good fit if you - Have **8+ years** building software with strong engineering fundamentals across the stack (data pipelines, tooling, and interfaces) - Have built real systems with large language models (agents, tool use, and/or evaluations) - Have worked on technical problems in a science or engineering field (e.g., physics, materials, chemistry, electrical or mechanical engineering) - Have a track record of **zero-to-one** work in startup or startup-like environments - Can work directly with expert users, deeply understand workflows, and stay focused on building the right system (not just the first requested one) - Have good judgment about what can/can’t be verified and are comfortable saying results aren’t good enough yet - Bring high agency, learn new domains quickly, and hold strong opinions loosely - Communicate clearly with researchers, engineers, and external partners, and care about the societal impacts of your work ## Strong candidates may also have - An advanced degree or research experience in a physical science or engineering field - Hands-on experience with scientific computing, simulation, numerical methods, or optimization - Experience in industrial R&D, a national lab, or a deep-tech company (energy, materials, manufacturing, hardware) - Experience building alongside customers/technical partners (e.g., forward-deployed applied AI or solutions engineering), ideally owning the resul
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