Backend Distributed Systems and Databases Expert

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

Job summary

Vraify is seeking contributors to help identify and fix issues in backend distributed systems. This remote, project-based role pays up to $45/hour and rewards strong engineering judgment and testing discipline.

You will create, solve, or review realistic tasks involving APIs, concurrency, distributed systems, storage engines, and databases, and you will write clear explanations of failures with reproducible evidence.

Qualifications

• Strong practical depth in APIs, concurrency, distributed systems, storage engines, databases, reliability, and performance.
• Clear written English communication.
• Verifiable evidence such as meaningful GitHub work, shipped software, a portfolio.
• Prior AI-evaluation experience useful but not required; strong engineering judgement and testing discipline.

Responsibilities

• Create, solve, or review realistic tasks involving APIs, concurrency, distributed systems, storage engines, databases, reliability, and performance.
• 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.

Skills

APIs

Concurrency

Distributed systems

Storage engines

Databases

Reliability

Performance

Job description

Help us find where advanced coding agents break in backend distributed systems and databases. 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 APIs, concurrency, distributed systems, storage engines, databases, reliability, and performance.
• 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 APIs, concurrency, distributed systems, storage engines, databases, reliability, and performance.
• 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.