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We are staffing a frontier AI data initiative that requires strong software engineers to build the infrastructure and training data used to develop and evaluate AI agents.

Key Responsibilities:

The Engineer will, depending on assigned track: build Python backend applications that replicate existing SaaS tools (such as Slack, Linear, Jira, Notion, Gmail, and wikis), including implementing integrations and standing up full-service backend functionality.
Perform thorough backend testing and integration validation to ensure each connector behaves faithfully like the system it emulates.
Adapt and extend previously built connectors as needed, and test existing connectors internally before they are treated as complete; Build new connectors from scratch where required, within agreed delivery timeframes.
Conduct data mining and task mining to identify representative workflows suitable for long-horizon task development; Author realistic tasks derived from mined data and workflows.
Verify task and data quality, realism, and correctness through structured QA; Write clear evaluation rubrics that define correct, partially correct, and deficient work.
Use AI coding agents proficiently throughout all development, QA, and validation work; collaborate across the connectors and tasks tracks.
Participate in onboarding, calibration, and quality-review cycles; deliver assigned work to the expected quality bar and on agreed milestones.

Must Have Required Skills:

Minimum 3+ years of overall experience.
Strong proficiency in Python (FastAPI, Flask, or Django)with proven experience in backend software development.
Proficiency with Git, Docker, and basic software pipeline setup.
Experience building scalable backend applications, REST APIs, and microservices.
Proficiency in using AI coding assistants (e.g., Codex, Claude Code, Cursor, GitHub Copilot, or similar) as part of daily development workflows.
Strong understanding of software engineering best practices, including version control, testing, and code quality.
Strong analytical and problem-solving skills with attention to detail.
Ability to work independently while collaborating effectively within distributed engineering teams.
Excellent written and verbal communication skills.

Nice to have:

Experience building connectors or integrations for SaaS platforms.
Knowledge of evaluation frameworks, QA methodologies, and rubric creation for AI datasets.
Experience developing realistic workflows for long-horizon AI tasks.

Offer details

Commitments required: Must complete and get approved minimum of 1 task per day.
Payment: $300/Task.
Engagement type: Contractor - Pay per Task.
Duration of contract: 2-3 weeks and start date ASAP.

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