Software Engineer, Staff: Applied AI, Science & Engineering

Software Engineer, Staff: Applied AI, Science & Engineering

Builds LLM-driven agents and integrations for scientific workflows using Claude and related evaluation tooling.

About the Role

Staff Software Engineer on the Applied AI, Science & Engineering team building systems that let Anthropic’s Claude model perform real scientific and engineering research workflows. You will prototype with domain experts, integrate simulation and scientific computing tools, and productionize agent harnesses and evaluation pipelines to make Claude useful and verifiable in partner settings.

Job Description

Role

This is an engineering-first Staff Software Engineer role on the Applied AI, Science & Engineering team. You will build agent harnesses, integrations, and evaluation systems that allow Anthropic’s Claude model to carry scientific and engineering problems from literature review through simulation, analysis, and iterative design. The role requires close collaboration with domain experts and partner organizations and focuses on shipping robust, reusable systems rather than one-off recommendations.

Key Responsibilities

• Build agent harnesses and research loops to take problems from literature review through hypothesis generation, simulation, analysis, and design iteration.
• Connect scientific computing and simulation tools (e.g., finite element, CFD, electromagnetic, molecular modeling codes) so Claude can drive them reliably and at scale.
• Design and implement evaluations that measure whether Claude’s outputs are correct and identify limitations.
• Work closely with scientists and engineers at partner organizations to turn open-ended problems into well-specified, verifiable tasks with clear success criteria.
• Prototype with partners, ship pilots into their workflows, and iterate on what actually moves the problem forward.
• Generalize successful approaches into shared tools, reusable components, and documented processes.
• Communicate technical performance, limits, and tradeoffs to researchers, engineering leads, and non-technical stakeholders.
• Partner with research and product teams to surface model shortcomings and influence future work.

Requirements

• 8+ years of software engineering experience with strong fundamentals and comfort across the stack (data pipelines, tooling, quick interfaces).
• Experience building systems that use large language models, including agents, tool use, or evaluations.
• Experience working on technical problems in a science or engineering field (for example, physics, materials, chemistry, electrical or mechanical engineering) is strongly preferred.
• Track record of zero-to-one work in startup or startup-like environments.
• Ability to work directly with expert users, deeply understand workflows, and focus on building the right systems.
• Strong judgment about what can be verified and clear communication skills with technical and non-technical stakeholders.
• High agency, ability to learn new domains quickly, and comfort holding strong opinions loosely.

Strongly Preferred / Nice-to-Have

• 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, national labs, or deep‑tech companies (energy, materials, manufacturing, hardware).
• Experience building alongside customers or technical partners and owning the resulting software.
• Experience with ML research, reinforcement learning environments, or evaluation design.

Compensation & Logistics

• Annual salary range: $405,000 — $485,000 USD.
• Minimum education: Bachelor’s degree or equivalent experience.
• Location policy: Anthropic expects staff to be in one of its offices at least 25% of the time (hybrid). Anthropic is headquartered in San Francisco.
• Visa sponsorship: Anthropic may sponsor visas and provides immigration legal support where applicable.

Claude Large Language Models (LLMs) Finite Element (FEM) tools Computational Fluid Dynamics (CFD) tools Electromagnetic simulation tools Molecular modeling codes Scientific computing RL environments Numerical methods Optimization

Skills

Software Engineering Fundamentals System Design Rapid Prototyping Scientific Computing Integration Evaluation Design Experimentation Cross‑functional Communication Partner/Customer Engagement Problem Decomposition Domain Adaptation Technical Leadership Collaboration Decision Making

Experience Level

USD 405,000 - 485,000/year

• Competitive compensation and benefits
• Optional equity donation matching
• Parental leave
• Flexible working hours
• Lovely office space
• Hybrid work (expected in‑office ≥25% of time)