Job description Our client is staffing a large frontier-AI data initiative and is seeking experienced backend software engineers to build infrastructure, integrations, and high-quality training and evaluation tasks for AI agents.
What You'll Do
- Build Python backend applications that replicate SaaS tools such as Slack, Linear, Jira, Notion, Gmail, and wikis.
- Implement integrations and full-service backend functionality, then test connectors for faithful behavior.
- Extend existing connectors or build new ones within agreed delivery timelines.
- Mine data and workflows to identify realistic long-horizon tasks for AI agents.
- Author tasks, validate their quality and realism, and write clear evaluation rubrics.
- Use AI coding assistants throughout development, testing, QA, and validation.
- Participate in onboarding, calibration, and quality-review cycles.
Requirements
- At least 3 years of backend software-engineering experience.
- Strong Python proficiency using FastAPI, Flask, or Django.
- Proficiency with Git, Docker, REST APIs, microservices, testing, and code-quality practices.
- Regular use of AI coding assistants such as Claude Code, Codex, Cursor, GitHub Copilot, or similar tools.
- Strong English communication, analytical judgment, and ability to work independently in a distributed team.
- Ability to complete at least one approved task per day during the 2-3 week engagement.
- Ability to complete a Python and Docker assessment after approval.
Nice to Have
- SaaS connector or integration experience.
- AI-data evaluation, QA methodology, or rubric-writing experience.
- Experience developing realistic workflows for long-horizon AI tasks.
Compensation
$300 USD per approved task. Each task may take approximately 5-10 hours, with an expected completion time of about 6 hours. Payment is based on approved tasks, not hours worked.
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