Software Engineer, Staff: Applied AI, Science & Engineering
Remote • New York City, NY; San Francisco, CA; Seattle, WA
Posted 6h ago
Job Location
New York City, NY; San Francisco, CA; Seattle, WA
Tech Stack
Remote Work Policy
Fully remote
Categories
Applied AI Engineer
About the job
Anthropic is building AI systems that are safe, beneficial, and transformative, with the mission to develop AI that benefits humanity. The Applied AI, Science & Engineering team bridges the gap between research breakthroughs and real-world applications by taking Claude to scientists and engineers working on hard problems in fields like energy, materials, and hardware design. This role focuses on building the software, agent harnesses, integrations, and evaluations that enable Claude to perform real research and engineering work. Engineers will work closely with domain experts, prototype quickly, and focus on building repeatable systems. While a science or engineering background is a plus, the ability to earn trust, translate fuzzy problems into concrete tasks, and ship is paramount.
Responsibilities
- Build agent harnesses and research loops for Claude to manage problems from literature review to design iteration.
- Integrate scientific computing and simulation tools (e.g., finite element, CFD, electromagnetic, molecular modeling) for Claude's use.
- Design and build evaluations to assess the accuracy of Claude's work.
- Collaborate with scientists and engineers to understand their problems, data, tools, and constraints, defining verifiable tasks.
- Prototype with partners, integrate solutions into their workflows, and iterate based on progress.
- Develop shared tools, reusable components, and documented processes from successful engagements.
- Communicate Claude's performance, limitations, and tradeoffs to researchers, engineering leads, and stakeholders.
- Liaise with research and product teams to report model shortcomings in science and engineering work and influence future development.
Requirements
- 8+ years of software development experience with strong engineering fundamentals across the stack.
- Experience building systems with large language models, including agents, tool use, or evaluations.
- Experience with technical problems in a science or engineering field (e.g., physics, materials, chemistry, engineering).
- Proven track record of zero-to-one work in startup or startup-like environments.
- Ability to work directly with expert users, understand their workflows, and focus on building the right system.
- Good judgment regarding verifiability and comfort in stating when results are insufficient.
- High agency, ability to quickly learn new domains, and flexibility in opinions.
- Clear communication with researchers, engineers, and external partners.
- Care about the societal impacts of AI work.