Bash Quality Assurance Lead

As a Bash Quality Assurance Lead, you will review AI-generated shell scripts, command-line workflows, automation snippets, debugging responses, and explanations. You will check whether the work is correct, safe, portable, and aligned with project rubrics.

You will also review trainer and QA work, give clear written feedback, support contributors with Bash review standards, and help improve consistency across shell-scripting training projects.

• Review Bash scripts, CLI workflows, automation snippets, debugging responses, and technical explanations.
• Check for quoting mistakes, portability problems, unsafe or destructive commands, missing error handling, security risks, and hallucinated command flags.
• Evaluate trainer and QA work against project guidelines and rubrics.
• Share clear feedback and help resolve recurring quality issues.
• Support onboarding and maintain style guides, FAQs, trackers, examples, honeypots, and calibration materials.
• Help improve QA processes and contributor consistency.

This is a remote, part-time contractor role for an experienced Bash or shell-scripting reviewer. The project is intended for someone who can make careful technical judgments and explain them clearly in writing.

• Pay: Up to $65 USD per hour.
• Workload: About 20 hours per week for 1 to 3 months.
• Location: United States only; remote work.
• Language: Clear written English is required.
• Experience: Expert-level Bash or shell scripting skills with Linux or Unix systems experience.
• Relevant background: Automation, DevOps, systems administration, CI/CD, technical support, or code review workflows.
• You must be able to identify unsafe commands, poor quoting, non-portable syntax, hallucinated flags, and destructive operations.
• You should be comfortable using Discord, Google Sheets, Google Docs, GitHub, dashboards, and project trackers.
• Experience with AI training, data annotation, large language model evaluation, code QA, or rubric-based review is a strong plus.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training work uses human reviewers to prepare examples and evaluate outputs that help artificial intelligence systems improve. People with strong technical skills are paid to spot errors, assess quality, and give reliable feedback that models and training teams can use.