C++ QA Lead - Remote
About the role
This role is a fast-growing AI Data Services company 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, compilable, efficient, safe, clearly explained, and aligned with client expectations.
Responsibilities
Spot-check C++ items, identify issues, provide feedback through DMs, and escalate recurring or critical quality problems.
Evaluate AI-generated C++ code, debugging responses, algorithmic solutions, tests, explanations, and performance recommendations.
Update contributors on Discord about guideline changes, workflow updates, and C++-specific review standards.
Respond to questions around memory safety, compilation, templates, STL usage, concurrency, complexity, testing, and rubric interpretation.
DM inactive contributors, track follow-ups, and flag availability issues.
Create and maintain C++ style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials.
Run onboarding/training calls covering project expectations, rubrics, and C++ quality standards.
Flag unsafe, non-compilable, misleading, inefficient, or non-production-ready C++ recommendations.
Identify recurring quality gaps and build scalable QA processes.
Requirements
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Computer Engineering, 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++ development, systems programming, performance engineering, embedded software, backend engineering, code review, QA, or technical mentoring.
Strong understanding of modern C++ standards, RAII, smart pointers, templates, STL containers/algorithms, object lifetime, move semantics, concurrency, exceptions, memory management, and build systems.
Ability to identify issues such as undefined behavior, memory leaks, dangling references, race conditions, inefficient algorithms, non-compilable code, hallucinated APIs, or incomplete explanations.
Familiarity with CMake, GCC/Clang/MSVC, GDB/LLDB, sanitizers, Valgrind, GoogleTest, Catch2, Boost, GitHub, CI/CD, profiling, and static analysis tools is preferred.
Experience leading or supporting remote teams of trainers, reviewers, engineers, coding mentors, or QAs is strongly preferred.
Highly organized and able to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and quality documentation.
Experience with AI training, data annotation, LLM evaluation, code QA, or rubric-based code review is a strong plus.