Kotlin Team Lead

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

You will assess work for code correctness, type safety, coroutine behavior, Android/JVM awareness, 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 Kotlin quality leadership will help ensure Kotlin training data is accurate, executable, idiomatic, 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.

Requirements: - Bachelor’s or Master’s degree in Computer Science, Software Engineering, IT, or equivalent professional experience. - Strong grasp of English to follow guidelines and provide clear technical feedback. - 3+ years of professional experience in Kotlin, Android development, JVM backend development, code review, QA, or technical mentoring. - Strong understanding of Kotlin syntax, null safety, data classes, sealed classes, generics, extension functions, collections, lambdas, coroutines, flows, exception handling, and interoperability with Java. - Ability to identify issues such as incorrect coroutine usage, non-idiomatic Kotlin, unsafe null handling, flawed logic, non-executable code, hallucinated APIs, or incomplete explanations. - Familiarity with Android, Jetpack Compose, Gradle, Ktor, Spring Boot, JUnit, MockK, Espresso, Kotlin Flow, GitHub, CI/CD, and app architecture patterns is preferred. - Experience leading or supporting remote teams of trainers, engineers, reviewers, or QAs is strongly preferred. - Comfortable with Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and PM systems. - Highly organized and able to maintain style guides, trackers, FAQs, honeypots, calibration tasks, and onboarding materials. - Experience with AI training, LLM evaluation, code QA, or rubric-based code review is a strong plus.