Software Engineer

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.

Responsibilities:

• The Engineer will, depending on the 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.

Requirements:

• 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.