Java QA Lead - Remote

About the role

This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Java quality leadership will help ensure Java training data is accurate, executable, idiomatic, secure, clearly explained, and aligned with client expectations.

Responsibilities

• Quality monitoring: Spot-check Java items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues.

• Code review: Evaluate AI-generated Java code, Spring/backend snippets, debugging responses, algorithmic solutions, tests, architecture explanations, and step-by-step reasoning.

• Trainer and QA communication: Update contributors on Discord about guideline changes, workflow updates, and Java-specific review standards.

• Question handling: Respond to questions around Java syntax, OOP design, collections, streams, concurrency, exceptions, Spring Boot, testing, security, and rubric interpretation.

• Trainer/QA activation management: DM inactive contributors, track follow-ups, and flag availability issues.

• Documentation: Create and maintain Java style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials.

• Onboarding and training: Run onboarding/training calls for Java contributors.

• Risk and security review: Flag insecure, misleading, non-compilable, inefficient, or non-production-ready Java recommendations.

• Process improvement: Identify recurring quality gaps and improve QA workflows.

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 Java development, backend engineering, enterprise software, JVM systems, code review, software QA, or technical mentoring.

• Strong understanding of Java fundamentals such as OOP, collections, generics, streams, lambdas, exceptions, concurrency, annotations, JVM behavior, memory management, modules/packages, and modern Java features.

• Ability to evaluate Java content against detailed rubrics and identify issues such as non-compilable code, incorrect logic, poor exception handling, unsafe concurrency, weak object modeling, inefficient algorithms, hallucinated APIs, or incomplete explanations.

• Familiarity with common Java ecosystems and tools such as Spring Boot, Maven, Gradle, JUnit, Mockito, Hibernate/JPA, REST APIs, JDBC, IntelliJ/Eclipse, Docker, GitHub, CI/CD, logging, and profiling tools 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.