Staff RL Data Platform Engineer — Full-Stack & Data Pipelines

Anthropic Limited; San Francisco, Northern (CA, KY); Hybrid; USD 320,000 - 405,000; Full time

Benefits offered by this job

Equity donation matching

Generous vacation & parental leave

Flexible working hours

Job summary

Anthropic Limited is seeking a Staff+ Software Engineer for its RL Data Platform in San Francisco. You will own end-to-end data collection and feedback pipelines, building web interfaces for annotators and robust backend services that RL researchers rely on daily.

You’ll lead cross-team collaborations, design scalable data flows, and ensure reliability and low latency at scale. The role emphasizes ownership, impact, and applying AI tools responsibly across the data lifecycle.

Qualifications

• Bachelor’s degree or equivalent combination of education, training, and/or experience.
• Experience building annotation, labelling, evaluation, or other human-in-the-loop tooling is a plus.
• Strong full-stack capabilities with production experience in TypeScript/React and Python.

Responsibilities

• Design, build, and operate interfaces used by annotators, domain experts, and researchers.
• Develop backend services, APIs, and data pipelines for model feedback flows.
• Own reliability, latency, and usability of live-endpoint systems.
• Collaborate with RL researchers to translate data needs into campaigns and tooling.
• Build dashboards and tooling to monitor data quality and throughput.
• Identify bottlenecks between data requests and training integration.

Skills

Full-stack eng

TypeScript/React

Python

Backend services

Data pipelines

System design

Stakeholder comms

Education

Bachelor's degree

Tools

TypeScript

React

Python

Job description

Anthropic Limited is seeking a Staff+ Software Engineer for its RL Data Platform in San Francisco. You will own end-to-end data collection and feedback pipelines, building web interfaces for annotators and robust backend services that RL researchers rely on daily.

You’ll lead cross-team collaborations, design scalable data flows, and ensure reliability and low latency at scale. The role emphasizes ownership, impact, and applying AI tools responsibly across the data lifecycle.