Model Performance Software Engineer, Claude Code

About Anthropic 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. About the Role We're looking for a Staff Software Engineer to set technical direction at the intersection of engineering and research on the Claude Code team. In this role, you'll partner directly with Anthropic's researchers and engineering leadership to shape how we measure, understand, and improve Claude's coding capabilities. You'll architect the systems, tooling, and evaluation infrastructure that determine how quickly our research can move—and you'll be accountable for the technical decisions that ripple across the team and beyond. This is a senior individual contributor role for someone who has already built and owned systems at significant scale, and who is ready to operate as a technical leader: driving architecture, mentoring engineers, and influencing the direction of Claude Code itself. Responsibilities - Set technical direction for evaluation systems, research infrastructure, and internal tooling across the Claude Code team - Architect eval frameworks that measure model capabilities across diverse coding tasks and scale with our research roadmap - Lead the design of infrastructure that enables researchers to run experiments at scale, and make the foundational tradeoffs that shape how the team operates for years - Identify the highest-leverage engineering investments—often before anyone has asked for them—and drive them to completion - Serve as a senior technical bridge between product and research, using strong product intuition to influence which capabilities we prioritize and how we measure progress against them - Mentor and raise the bar for other engineers on the team; review designs, unblock peers, and model the engineering standards we want to scale - Partner with research leads to translate ambiguous research questions into durable engineering solutions - Own critical systems end-to-end, from architecture through production reliability, and take responsibility for their long-term health You may be a good fit if you: - Have 10+ years of software engineering experience, with a track record of operating as a Staff or Principal engineer (or equivalent) at a high-caliber organization - Have architected and owned complex, high-stakes systems—pipelines, infrastructure, or platforms that orchestrate many components, handle significant state and logic, and serve multiple teams - Have a history of setting technical direction that others follow—through design docs, architectural decisions, or technical strategy that shaped how a team or org operates - Thrive in high-intensity environments with fast iteration cycles, and have the judgment to know when to move fast and when to invest in durability - Take full ownership of ambiguous, open-ended problems and drive them to completion with minimal direction - Are a power user of agentic coding tools with deep intuition about model capabilities and limitations - Can dive into unfamiliar technical domains—ML systems, research workflows, novel infrastructure—and get to the frontier quickly - Care deeply about correctness and reliability, and have raised engineering standards on teams you've been part of - Are energized by working at the boundary between engineering and AI research, and by the prospect of influencing both Strong candidates may also have experience with: - Designing or scaling eval/evaluation frameworks for ML systems - Reinforcement learning infrastructure or training systems - Leading technical initiatives in high-performance, demanding environments—trading firms, quant funds, frontier research labs, or fast-moving startups where intensity and technical excellence are the norm - Research computing, scientific infrastructure, or developer platforms at scale - A strong quantitative foundation (math, physics, or related fields) - Expertise in Python and TypeScript The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of t

10+ years of software engineering experience, with a track record of operating as a Staff or Principal engineer (or equivalent) at a high-caliber organization. Architected and owned complex, high-stakes systems—pipelines, infrastructure, or platforms that orchestrate many components, handle significant state and logic, and serve multiple teams. History of setting technical direction that others follow—through design docs, architectural decisions, or technical strategy that shaped how a team or org operates. Thrive in high-intensity environments with fast iteration cycles, and have the judgment to know when to move fast and when to invest in durability. Take full ownership of ambiguous, open-ended problems and drive them to completion with minimal direction. Are a power user of agentic coding tools with deep intuition about model capabilities and limitations. Can dive into unfamiliar technical domains—ML systems, research workflows, novel infrastructure—and get to the frontier quickly. Care deeply about correctness and reliability, and have raised engineering standards on teams you've been part of. Are energized by working at the boundary between engineering and AI research, and by the prospect of influencing both. Strong candidates may also have experience with designingscale eval/evaluation frameworks for ML systems, reinforcement learning infrastructure or training systems, leading technical initiatives in high-performance, demanding environments, research computing, scientific infrastructure, or developer platforms at scale, and have a strong quantitative foundation (math, physics, or related fields). Expertise in Python and TypeScript.

Set technical direction for evaluation systems, research infrastructure, and internal tooling across the Claude Code team. Architect eval frameworks that measure model capabilities across diverse coding tasks and scale with our research roadmap. Lead the design of infrastructure that enables researchers to run experiments at scale, and make the foundational tradeoffs that shape how the team operates for years. Identify the highest-leverage engineering investments—often before anyone has asked for them—and drive them to completion. Serve as a senior technical bridge between product and research, using strong product intuition to influence which capabilities we prioritize and how we measure progress against them. Mentor and raise the bar for other engineers on the team; review designs, unblock peers, and model the engineering standards we want to scale. Partner with research leads to translate ambiguous research questions into durable engineering solutions. Own critical systems end-to-end, from architecture through production reliability, and take responsibility for their long-term health.