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Anthropic

Software Engineer, RL Data

Anthropic

Software Engineer developing high-quality reinforcement learning data systems for AI at Anthropic. Involves collaboration, data collection, and infrastructure engineering.

Posted 6/2/2026full-timeLondon • California, New York • 🇺🇸 United StatesMid-LevelSenior💰 $320,000 - $485,000 per yearWebsite

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Hard Skills
software engineeringprogramming languagebackend systemsinfrastructuredata collection pipelinesQA frameworkssandboxingsnapshottingtool coverageAI tools
Soft Skills
proactive communicationopen communicationproblem ownershiptrustworthinessadaptabilityiterative developmentcollaborationsupportescalationsensitivity to societal impacts
Industry Keywords
technical architecturereward hackingenvironment qualityhuman data collectionoperationssecuritycomplianceexternal data vendorsdesign pipelinesevals

About the role

Key responsibilities & impact
  • Own significant parts of our stack end-to-end, from technical architecture through the unglamorous operational work that makes it succeed
  • Build data collection pipelines, read the transcripts they produce, and iterate on prompts, evals, and graders until the output is good
  • Develop and improve QA frameworks to catch reward hacking and ensure environment quality
  • Build interfaces that make collecting human data fast and painless for the people providing it
  • Harden execution environments — sandboxing, snapshotting, tool coverage — so tasks hold up at training scale
  • Embed with the teams and domain experts who use our systems day-to-day: design pipelines and evals with them, support them directly, and ship the improvements they need
  • Work with operations, security, and compliance partners to roll our systems out to new users, and manage technical relationships with external data vendors

Requirements

What you’ll need
  • Strong software engineering skills and proficiency in at least one modern programming language
  • Experience designing, building, and running backend systems or infrastructure
  • Effective use of AI tools in your own day-to-day work
  • Willingness to own problems end-to-end, including the parts that aren't engineering
  • Proactive, open communication: you can be trusted to run a workstream, and to escalate early when something's off
  • Comfort iterating quickly in ambiguous, fast-changing situations
  • Care about the societal impacts of your work

Benefits

Comp & perks
  • competitive compensation and benefits
  • optional equity donation matching
  • generous vacation and parental leave
  • flexible working hours
  • lovely office space