C# Code Quality Assurance Lead

As a C# Quality Assurance Lead, you will review AI-generated code and trainer QA work against project guidelines. You will assess correctness, runtime behavior, type safety, async behavior, debugging accuracy, readability, maintainability, performance, security, test coverage, and instruction following.

You will also support contributors, improve review processes, and help keep quality standards consistent across C# training projects.

• Review C# code, .NET snippets, API examples, debugging responses, tests, architecture explanations, and step-by-step reasoning.
• Find incorrect logic, code that will not run, flawed async usage, weak error handling, type-safety problems, security risks, invented APIs, and incomplete explanations.
• Escalate recurring or serious quality issues and answer questions about .NET behavior, async/await, LINQ, dependency injection, EF Core, testing, security, and rubric interpretation.
• Create and maintain style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials.
• Lead onboarding and training calls for C# contributors and help improve QA workflows.
• Communicate with and support remote trainers, reviewers, engineers, coding mentors, or QA contributors.

What it pays and takes

This is an expert-level, part-time contract role for someone with a strong C# and .NET background. Experience in backend engineering, code review, QA, or technical mentoring is relevant.

• Pay: $75 per hour.
• Time: 20+ hours per week.
• Location: United States.
• Language: Strong English communication skills.
• Work type: Contractor and part time.
• Required: Deep knowledge of C# syntax, object-oriented programming, LINQ, generics, collections, exceptions, async/await, tasks, dependency injection, nullable reference types, records, delegates and events, and .NET runtime behavior.
• Preferred: Familiarity with .NET, ASP.NET Core, Entity Framework Core, xUnit, NUnit, MSTest, Visual Studio, Rider, NuGet, Azure, AWS, Docker, GitHub, CI/CD, and logging tools.
• Helpful: Experience with AI training, large language model evaluation, code QA, or rubric-based code review.
• Helpful: Comfort using Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems.

How it works

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

About AI training work

AI training work uses human judgment to review examples and model responses so artificial intelligence systems improve. Experienced software professionals are needed to assess code quality, explain problems clearly, and help models produce safer and more reliable results.