Go Team Lead, Code Quality Review

You will lead quality review for Go coding work used in AI training projects. This includes reviewing code, debugging answers, backend snippets, concurrency examples, tests, API implementations, and technical explanations.

You will also help improve review standards and support the people doing the work. The role combines detailed Go code evaluation with written feedback, onboarding support, documentation, and quality process improvement.

• Review Go responses for correctness, compilation, runtime behavior, concurrency safety, error handling, readability, maintainability, performance, security awareness, testing, formatting, and instruction-following.
• Identify issues such as non-compilable code, goroutine leaks, race conditions, weak error handling, inefficient logic, hallucinated APIs, and security problems.
• Assess backend code, HTTP servers, REST APIs, gRPC implementations, tests, and concurrency examples against detailed project rubrics.
• Give precise written feedback to trainers and QAs, communicate guideline updates, and help keep Go-specific guidance current.
• Support onboarding, calibration, FAQs, honeypots, style guides, trackers, and other quality documentation.
• Monitor recurring issues and help improve scalable QA processes for Go AI training work.

This is a remote, part-time contractor role for candidates in the United States. The work focuses on Go AI training projects and requires at least 20 hours per week.

• Pay: Up to $70 per hour.
• Location: Remote and open to candidates in the United States.
• Schedule: 20 or more hours per week.
• Work type: Contractor and part-time.
• Experience level: Intermediate.
• Language: Strong professional English communication skills.
• Required: Professional experience in Go development, backend engineering, code review, software QA, or technical mentoring.
• Required: Strong knowledge of goroutines, channels, interfaces, structs, methods, slices, maps, pointers, error handling, context, packages, modules, and testing.
• Required: Ability to assess work against detailed rubrics and identify correctness, safety, and maintainability issues.
• Tools and workflows: go test, gofmt, go vet, the race detector, HTTP servers, REST APIs, gRPC, Docker, Kubernetes, SQL drivers, GitHub, and CI/CD.
• Preferred: Experience supporting trainers, annotators, reviewers, engineers, coding mentors, or QAs, plus experience with AI training, data annotation, LLM evaluation, code QA, or rubric-based code review.
• Preferred: Experience working with remote teams.

Apply on OpenTrain with your resume, then complete the application on the hiring site. OpenTrain is where you find this role and start your application; it is not the employer or payer for the work.

AI training work is the human work behind many AI systems, including reviewing code, rating model responses, and preparing examples. People with strong technical experience are needed to judge whether model outputs are correct, safe, useful, and maintainable.