Staff Software Engineer (Applied AI, Science & Engineering)

Anthropic; Seattle (WA); On-site; USD 180,000 - 300,000; Full time

Benefits offered by this job

Comprehensive health, dental, and view

Fertility benefits

Parental leave (22 weeks)

Flexible paid time off

Mental health support

Salary and equity packages

Equity donation matching

Retirement plans with matching

Life and income protection

Wellness stipend

Commuter benefits

Education stipend

Home office stipends

Relocation support

Daily meals and snacks

Job summary

Anthropic is seeking an engineer to join the Applied AI, Science & Engineering team in Seattle. You will focus on building and hardening Claude-related systems, working closely with scientists and engineers to turn complex problems into repeatable, verifiable solutions.

You will prototype with partners, bring domain expertise to Claude deployments, and influence how Claude is applied to science and engineering problems across energy, materials, and hardware domains.

Qualifications

• 8+ years of software development experience, with strong engineering fundamentals.
• Hands-on experience building software in a science or engineering field.
• Excellent communication with researchers, engineers, and partners.

Responsibilities

• Be the technical voice on Claude's performance in science and engineering work.
• Prototype with partners, ship pilots, and integrate into workflows.
• Turn open questions into well-specified, verifiable tasks with clear success criteria.
• Partner with research and product teams to address model shortcomings and future directions.

Skills

Engineering fundamentals

8+ years software experience

Cross-functional communication

Research collaboration

Education

Advanced degree in physical science or engineering

Job description

• At Anthropic, we’re building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications


• Claude is getting good at research. Given a well-posed problem, it can read the literature, write and run simulations, analyze results, and iterate on a design across physics, materials, chemistry, and engineering. But most of the hardest problems in science and engineering aren’t well-posed. They live inside companies and labs with their own data, tools, constraints, and experts, and progress depends on turning all of that into work a model can actually do and check


• 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. We build the tools Claude needs to do real research and engineering work. Mostly that means software: the agent harnesses, integrations, evaluations, and working processes that turn a partner’s problem into something Claude can make progress on and validate. We find real-world problems and test what we build through partner engagements, then feed our learnings back to our research and product teams. It’s early, and the engineers who join now will shape how Claude gets applied to science and engineering


• This is an engineering role first. You’ll spend real time with domain experts, become the person who knows how to get Claude working in their field, and prototype quickly alongside them. Most of your time, though, goes into building and hardening the systems that make that work repeatable, not into writing recommendations or configuring someone else’s product. A science or engineering background is a big plus, but what matters most is that you can earn the trust of expert researchers, turn a fuzzy problem into something concrete and checkable, and ship


• 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 (finite element, CFD, electromagnetic, or molecular modeling codes, for example) 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

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents


• Inclusive fertility benefits via Carrot Fertility


• 22 weeks of paid parental leave


• Flexible paid time off and absence policies


• Mental health support for you and your dependents


• Competitive salary and equity packages


• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant


• Retirement plans with competitive matching


• Life and income protection plans


• $500/month flexible wellness and time saver stipend


• Commuter benefits


• Annual education stipend


• Home office stipends


• Relocation support for those moving for Anthropic


• Daily meals and snacks in the office

• 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


• Have a track record of zero-to-one work in startup or startup-like environments


• Have worked on technical problems in a science or engineering field, such as physics, materials, chemistry, or electrical or mechanical engineering


• 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 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 good judgment about what can and can’t be verified, and are comfortable saying a result isn’t good enough yet


• We encourage you to apply even if you do not believe you meet every single qualification


• 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 with ML research, RL environments, or evaluation design


• 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