Jobs · Engineering

Kotlin Team Lead

SME Careers · United States · 1 wk ago
RemoteRemoteEngineeringContract

Key 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

  • 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.

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