C# Team Lead

Pay: up to $75/hour

In this hourly, remote contractor role, you will work as a C# Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across C# AI training projects. You will review AI-generated C# code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards.

You will assess work for code correctness, runtime behavior, .NET ecosystem awareness, type safety, async behavior, debugging accuracy, readability, maintainability, performance, security, test coverage, formatting, instruction-following, and rubric adherence.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your C# quality leadership will help ensure C# training data is accurate, executable, idiomatic, secure, clearly explained, and aligned with client expectations.

Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Important:

There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Responsibilities

• Quality monitoring: Spot-check C# items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues.
• Code review: Evaluate AI-generated C# code, .NET snippets, API examples, debugging responses, tests, architecture explanations, and step-by-step reasoning.
• Trainer/QA communication: Update contributors on Discord about guideline changes, workflow updates, and C#-specific review standards.
• Question handling: Respond to questions around .NET behavior, async/await, LINQ, dependency injection, EF Core, testing, security, and rubric interpretation.
• Activation management: DM inactive contributors, track follow-ups, and flag availability issues.
• Documentation: Create and maintain C# style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding: Run onboarding/training calls for C# contributors.
• Risk review: Flag insecure, misleading, non-executable, or non-production-ready C#/.NET recommendations.
• Process improvement: Identify recurring gaps and improve QA workflows.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, IT, or equivalent professional software engineering experience.
• Strong grasp of English to follow guidelines and provide clear technical feedback.
• 3+ years of professional experience in C#/.NET development, backend engineering, enterprise software, cloud development, code review, QA, or technical mentoring.
• Strong understanding of C# syntax, OOP, LINQ, generics, collections, exceptions, async/await, tasks, dependency injection, nullable reference types, records, delegates/events, and .NET runtime behavior.
• Ability to identify issues such as incorrect logic, non-executable code, flawed async usage, poor error handling, weak type safety, security risks, hallucinated APIs, or incomplete explanations.
• Familiarity with .NET, ASP.NET Core, Entity Framework Core, xUnit/NUnit/MSTest, Visual Studio/Rider, NuGet, Azure/AWS, Docker, GitHub, CI/CD, and logging/observability tools is preferred.
• Experience leading or supporting remote teams of trainers, reviewers, engineers, coding mentors, or QAs is strongly preferred.
• Comfortable using Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and PM systems.
• Highly organized and able to maintain style guides, trackers, FAQs, onboarding materials, honeypots, calibration tasks, and quality documentation.
• Experience with AI training, LLM evaluation, code QA, or rubric-based code review is a strong plus.

Skills: LLM evaluation, Code review, C#, ASP.NET Core, Debugging, Testing, C# QA, Trainer Feedback, AI Training, .NET

Open to candidates in: The United States

Interview language: English