About The Role
Todas las habilidades, cualificaciones y experiencia relevantes que necesitará un candidato seleccionado se enumeran en la siguiente descripción.
This project is suited for a Senior Python developer with deep functional testing experience, strong Linux and Docker skills, the ability to read code across multiple languages with the support of LLMs (e.g., C, Rust, Go) and translate requirements for migration tasks, and confidence using tools like Roo Code or Claude Code to accelerate iterative development.
Key Responsibilities
Create functional black box tests for large codebases in various source languages.
Create and manage Docker environments to ensure 100% reproducible builds and test execution across different platforms.
Monitor code coverage and configure automated scoring criteria to meet industry benchmark-level standards.
Leverage LLMs (Roo Code, Claude) to accelerate development cycles, automate repetitive tasks, and improve overall code quality.
Requirements
5+ years of experience as a Software Engineer (primarily Python).
Deep experience with pytest (fixtures, session‑scoped, timeouts) and designing black‑box functional tests for CLI tools.
Expert‑level Docker skills (reproducible Dockerfiles, user contexts, secure workspaces).
Strong Linux & Bash scripting skills and comfort debugging inside containers.
Proficiency with modern Python tooling (uv, pyproject.toml, packaging).
Ability to read and understand many coding languages with LLMs (for example C, C++, Rust, or Go).
Experience using LLMs (Claude Code, Roo Code, Cursor) to accelerate iterative development and test‑case generation.
English language - B2 or higher.
Additional Requirements
Prior experience with agent evaluation platforms and MCP CLI.
Tools and Technologies
Python (pytest, uv, Pillow), Docker, Bash, Git Submodules, C/C++/Rust/Go (reading), Dagger, GitHub Codespaces, LLMs (Claude Code, Roo Code, Cursor),, gcov, kcov.
Benefits
Freelance project‑based collaboration via the Mindrift platform (powered by Toloka AI).
Fully remote and flexible participation — choose when and how much to contribute (20-30 hours per week).
Each project has its own compensation level based on scope and expertise required. On this project, AI trainers earn up to $30 per hour equivalent.
Opportunity to contribute to innovative AI projects for leading tech companies. xpzdshu
Supportive global community.
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