Software Engineer for AI Workflow Annotation

Role Overview

Help improve next-generation AI systems by creating realistic, multi-step software engineering workflows. You will draw on hands-on engineering experience to document how work is performed in GitHub and related tools. No prior AI experience is required.

Key Responsibilities

• Design and write detailed task scenarios based on authentic engineering activities, including pull request management, issue triage, merge conflict resolution, and CI configuration updates in GitHub.
• Complete and document workflows in real time using actual tools, capturing steps, rationale, edge cases, and decision points.
• Incorporate Slack, Microsoft 365 or Google Workspace, and Snowflake where appropriate to create end-to-end engineering scenarios.
• Prepare structured workflow documentation covering step order, intent, expected outcomes, and supporting visuals such as screenshots or logs when needed.
• Identify ambiguous or unrealistic scenarios, share them with the data program team, and refine workflows based on feedback.
• Submit deliverables and collaborate with project leads through an internal annotation platform.

Qualifications

• At least 2 years of professional software engineering experience with daily use of GitHub-centered workflows.
• Strong written English skills, with clear, consistent, detail-oriented process documentation.
• Practical experience using Slack and Microsoft 365 or Google Workspace in regular engineering work.
• Experience with code review, versioning, branching, or release workflows.
• Experience with CI/CD pipelines, code review platforms, or process-documentation systems is preferred.
• Basic SQL skills, ideally with Snowflake, are helpful but not required.
• Experience in data annotation, technical writing, or QA documentation is a plus.

Work Terms

• Remote contract engagement.

Compensation

• $14 to $36 per hour.