Remote Java QA Lead — Code Quality & Mentorship

About This Role

In this hourly, remote contractor role, you will work as a Java Quality Assurance Lead to oversee quality, consistency, and trainer performance across Java AI training projects. You will review AI-generated Java code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards. You will assess work for code correctness, compile-time validity, runtime behavior, object-oriented design, API usage, debugging accuracy, readability, maintainability, performance, security, test coverage, formatting, instruction-following, and adherence to project-specific rubrics.

This role requires strong Java expertise, English communication skills, excellent attention to detail, and the ability to manage quality workflows across remote technical teams. 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.

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.

Job Description

Job Title: Java Quality Assurance Lead

Job Type: Contract

Location: Remote

About This Role

In this hourly, remote contractor role, you will work as a Java Quality Assurance Lead to oversee quality, consistency, and trainer performance across Java AI training projects. You will review AI-generated Java code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards. You will assess work for code correctness, compile-time validity, runtime behavior, object-oriented design, API usage, debugging accuracy, readability, maintainability, performance, security, test coverage, formatting, instruction-following, and adherence to project-specific rubrics.

This role requires strong Java expertise, English communication skills, excellent attention to detail, and the ability to manage quality workflows across remote technical teams. 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.

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.

Your profile

• 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,…