# Staff+ Software Engineer, Infrastructure, Interpretability at Anthropic

- Company: Anthropic
- Status: Open
- Workplace: On-site
- Location: San Francisco, CA
- Level: Staff
- Discipline: Engineering
- Employment: Full-time
- Posted: 2026-08-12
- Skills: AI Research & Engineering
- Apply: https://job-boards.greenhouse.io/anthropic/jobs/5388612008

## Description

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:
 When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?"
 The Interpretability team at Anthropic works to understand what's actually happening inside trained models - and applies our best techniques to keep frontier AI safe as it rapidly improves.
 Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs.
 More resources to learn about our work: 
• 
 Our Research blog - covering advances including Monosemantic Features and Circuits 
• 
 An Intro to Interpretability from our research lead, Chris Olah 
• 
 The Urgency of Interpretability from CEO Dario Amodei
• 
 Engineering Challenges Scaling Interpretability - directly relevant to this role
• 
 60 Minutes segment - see a demo of tooling our team built
• 
 New Yorker article - what it's like to work on one of AI's hardest open problems
 This role is an early hire on a new infrastructure effort within Interpretability: you'll help define its charter, not just execute it. 
 Interpretability research requires deep access to frontier models while retaining a high degree of research flexibility. Your job is to build the paved 

More Anthropic roles: https://deviantjobs.com/companies/anthropic