Kotlin Team Lead

SME Careers; United States; Remote; USD 55,000 - 124,000; Part time

Job summary

SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, seeks a Kotlin Quality Assurance Lead (QAL) for an hourly remote contractor role to oversee Kotlin QA across AI training projects. You will review AI-generated Kotlin code and trainer/QA work to ensure quality and adherence to guidelines.

You will assess code correctness, type safety, coroutines, Android/JVM context, readability, performance, test coverage, and rubric adherence, providing precise feedback and

Qualifications

• Bachelor’s or Master’s degree in CS, SE, IT, or equivalent experience.
• Excellent English for following guidelines and providing clear technical feedback.
• 3+ years in Kotlin, Android, JVM backend, code review, QA, or mentoring.
• Strong Kotlin syntax, null safety, data classes, sealed classes, generics, extension functions, collections, lambdas, coroutines, flows, exception handling, and Java interoperability.
• Ability to flag non-idiomatic or non-executable Kotlin code.
• Familiarity with Android, Jetpack Compose, Gradle, Ktor, Spring Boot, JUnit, MockK, Espresso, Kotlin Flow, GitHub, CI/CD, and architecture patterns.
• 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.

Responsibilities

• Spot-check Kotlin items and provide ongoing feedback through DMs.
• Review AI-generated Kotlin code, Android/JVM snippets, coroutine workflows, tests, and explanations.
• Communicate guideline changes and Kotlin-specific standards on Discord.
• Answer questions around Kotlin syntax, null safety, coroutines, Android/JVM context, tests, packages, and rubric interpretation.
• DM inactive contributors and manage activation tracking.
• Create Kotlin documentation, style guides, examples, trackers, FAQs, honeypots, and onboarding materials.
• Run onboarding/training calls for Kotlin contributors.
• Flag insecure, misleading, non-executable, or non-production-ready Kotlin recommendations.
• Improve QA processes based on recurring quality gaps.

Skills

Kotlin

Android development

JVM backend

Code review

QA

Mentoring

English (strong)

Education

Bachelor’s or Master’s degree

Tools

GitHub

CI/CD

Gradle

Ktor

Spring Boot

JUnit

MockK

Espresso

Job description

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.

Responsibilities

• Spot-check Kotlin items and provide ongoing feedback through DMs.
• Review AI-generated Kotlin code, Android/JVM snippets, coroutine workflows, tests, and explanations.
• Communicate guideline changes and Kotlin-specific standards on Discord.
• Answer questions around Kotlin syntax, null safety, coroutines, Android/JVM context, tests, packages, and rubric interpretation.
• DM inactive contributors and manage activation tracking.
• Create Kotlin documentation, style guides, examples, trackers, FAQs, honeypots, and onboarding materials.
• Run onboarding/training calls for Kotlin contributors.
• Flag insecure, misleading, non-executable, or non-production-ready Kotlin recommendations.
• Improve QA processes based on recurring quality gaps.

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.