Software Engineer, Staff: Applied AI, Science & Engineering

New York City, NY · San Francisco · Seattle, WA · USD 405,000-485,000 / year · 8+ years experience · Hybrid · Posted Oct 6, 2026

At a glance

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

At Anthropic, we're building AI systems that are safe, beneficial, and transformative, bridging the gap between research breakthroughs and real-world applications.
Our Applied AI, Science & Engineering team takes Claude to the scientists and engineers working on hard problems in energy, materials, hardware design, and other physical-world fields.
This is an engineering role first where you will spend real time with domain experts, prototype quickly alongside them, and build and harden the systems that make that work repeatable.

Build the agent harnesses and research loops that let Claude carry a problem from literature review through hypothesis generation, simulation, analysis, and design iteration
Connect scientific computing and simulation tools so Claude can drive them reliably and at scale
Design and build evaluations that tell us whether Claude's work is actually right, and be honest about where it isn't
Sit with scientists and engineers at partner organizations to learn their problem, data, tools, and constraints, and turn open-ended questions into well-specified, verifiable tasks with clear success criteria
Prototype with partners, ship pilots into their workflows, and cut anything that doesn't move the problem forward
Turn what works in one engagement into shared tools, reusable components, and documented processes the next one can start from
Be the technical voice on how Claude performs on science and engineering work, explaining results, limits, and tradeoffs clearly to researchers, engineering leads, and non-technical stakeholders alike
Partner with our research and product teams to share where models fall short on science and engineering work, and help shape what comes next

Have 8+ years of experience building software, with strong engineering fundamentals and comfort across the stack, from data pipelines to tooling to quick interfaces
Have built real systems with large language models, including agents, tool use, or evaluations
Have worked on technical problems in a science or engineering field, such as physics, materials, chemistry, or 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, understand their workflows deeply, and still keep the focus on building the right system rather than the one first requested
Have good judgment about what can and can't be verified, and are comfortable saying a result isn't good enough yet
Bring high agency, pick up 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

An advanced degree or research experience in a physical science or engineering field
Hands-on experience with scientific computing and simulation, numerical methods, or optimization
Experience in industrial R&D, a national lab, or a deep-tech company in areas like energy, materials, manufacturing, or hardware
Experience building alongside customers or technical partners, for example in forward-deployed, applied AI, or solutions engineering roles, ideally where you also owned the software that came out of it
Experience with ML research, RL environments, or evaluation design