Go QA Lead - Remote
About the role
This is a remote contractor role as a Go Quality Assurance Lead. The role involves overseeing quality, consistency, and trainer performance across Go AI training projects. You will review AI-generated Go code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards.
Responsibilities
Spot-check Go items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
Evaluate AI-generated Go code, debugging responses, backend snippets, concurrency examples, tests, API implementations, and technical explanations for correctness and clarity.
Update trainers/QAs on Discord about guideline changes, workflow updates, and Go-specific quality expectations.
Respond to trainer/QA questions around Go syntax, concurrency, error handling, context usage, interfaces, testing, performance, security, and rubric interpretation.
DM inactive contributors, encourage activation, track follow-ups, and flag availability issues.
Create and maintain Go style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials.
Schedule and run onboarding/training calls with contributors to explain project expectations, workflows, rubrics, and Go review standards.
Flag insecure, misleading, non-compilable, race-prone, or non-production-ready Go recommendations.
Identify recurring quality gaps and help build scalable QA processes for Go AI training projects.
Requirements
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or equivalent professional software engineering experience.
Strong grasp of English to follow guidelines, communicate with teams, and provide clear technical feedback.
3+ years of professional experience in Go development, backend engineering, cloud services, distributed systems, DevOps tooling, code review, software QA, or technical mentoring.
Strong understanding of Go fundamentals such as goroutines, channels, interfaces, structs, methods, slices, maps, pointers, error handling, context, packages/modules, testing, and idiomatic Go style.
Ability to evaluate Go content against detailed rubrics and identify issues such as non-compilable code, incorrect concurrency patterns, goroutine leaks, race conditions, poor error handling, inefficient logic, hallucinated APIs, or incomplete explanations.
Familiarity with common Go tools and ecosystems such as go test, gofmt, go vet, race detector, Go modules, HTTP servers, REST APIs, gRPC, Docker, Kubernetes, SQL drivers, GitHub, CI/CD, and cloud-native workflows is preferred.
Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, coding mentors, or QAs is strongly preferred.
Highly organized and able to maintain style guides, trackers, FAQs, 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.