Repository Software Engineering Expert

Vraify; Deutschland; Remote; EUR 46,000 - 65,000; Full time

Benefits offered by this job

Remote work

Job summary

Vraify is seeking contributors for remote, project-based work focused on advanced coding tasks, repository review, and robust testing. You will create or solve realistic tasks, stress-test generated code, and document failures with reproducible evidence.

Applicants should show strong engineering judgment, clear written English communication, and verifiable GitHub or portfolio evidence. Remote work is offered with competitive hourly rates depending on project and expertise.

Qualifications

• Strong practical depth in real multi-file repositories and regression testing.
• Ability to navigate unfamiliar code or specifications and communicate decisions clearly in English.
• Verifiable evidence such as GitHub work, shipped software, or a portfolio.

Responsibilities

• Create, solve, or review tasks involving real multi-file repositories and maintainability.
• Test AI-generated code and traces for correctness and edge cases.
• Write tests, patches, and explanations of failure modes.
• Review peer-authored tasks for realism and evaluation criteria.

Skills

Real multi-file repos

Issue diagnosis

Regression tests

Maintaining code quality

Job description

Help us find where advanced coding agents break in repository software engineering. Build or solve realistic tasks, stress-test generated code, and explain failures with reproducible evidence. Remote project-based work can pay up to $45/hour, depending on the project and demonstrated expertise.

What you'll do:

• Create, solve, or review realistic tasks involving real multi-file repositories, issue diagnosis, code changes, regression tests, and maintainability.
• Test AI-generated code and agent traces for correctness, edge cases, regressions, unsafe assumptions, and incomplete fixes.
• Write strong tests, reference patches, expected outcomes, and concise explanations of the failure mode.
• Review peer-authored tasks for realism, reproducibility, difficulty, and clean evaluation criteria.

What we look for:

• Strong practical depth in real multi-file repositories, issue diagnosis, code changes, regression tests, and maintainability.
• Ability to navigate unfamiliar code or specifications and communicate technical decisions in clear written English.
• Verifiable evidence such as meaningful GitHub work, shipped software, a competition profile, technical writing, or a portfolio. Confidential industry work can be described in the application without exposing proprietary material.
• Prior AI-evaluation experience is useful but not required; strong engineering judgement and testing discipline matter more.