We are sharing a specialised part-time consulting opportunity for experienced software engineers with strong expertise in Python, Java, Rust, C++, Go, TypeScript, algorithms, debugging, refactoring, and performance optimisation to contribute to an advanced AI training project involving Model Context Protocol (MCP) environments.
Selected professionals will create reinforcement-learning environments that test an AI model's ability to solve complex software-engineering problems using MCP tools and real server interactions. The work combines practical software engineering, deterministic evaluation design, and the creation of high-quality reference solutions. No prior experience in AI is required.
Key Responsibilities
MCP Environment Development
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Create reinforcement-learning environments based on realistic software-engineering tasks
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Design scenarios requiring agents to discover and reason over information from MCP servers
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Build tasks involving real tool interactions rather than isolated code-generation exercises
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Ensure environments accurately measure both MCP tool use and engineering capability
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Maintain reproducibility across evaluation runs
Software Engineering Task Design
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Create challenging tasks involving bug fixing, feature implementation, refactoring, and performance optimisation
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Develop scenarios that require meaningful reasoning across existing codebases
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Design tasks that test algorithms, data structures, debugging, and architectural judgement
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Ensure problems reflect realistic engineering constraints and workflows
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Balance task complexity with clear, measurable success criteria
Golden Solutions & Deterministic Verification
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Create high-quality golden reference solutions for evaluation tasks
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Develop deterministic verification logic that reliably distinguishes correct from incorrect implementations
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Define clear acceptance criteria for software behaviour and task completion
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Validate environments against edge cases and unintended solution paths
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Ensure evaluation logic remains stable and reproducible
Code Quality & Performance Engineering
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Debug complex software issues across multiple programming languages
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Implement maintainable features in existing codebases
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Refactor code while preserving intended functionality
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Identify and resolve performance bottlenecks
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Apply scalability, maintainability, and software-quality best practices
Technical Review & Collaboration
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Review task quality, code correctness, and evaluation robustness
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Communicate technical decisions and assumptions clearly
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Participate in collaborative review of software-engineering environments
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Contribute to code-review standards and engineering best practices
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Work effectively in remote and cross-functional technical teams
Ideal Profile
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Strong proficiency in one or more of C++, Python, Java, Go, TypeScript, or Rust
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Deep understanding of algorithms, data structures, and performance optimisation
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Demonstrated experience debugging complex software issues
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Strong background in feature development and codebase refactoring
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Proven ability to improve software performance and scalability
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Experience working with large or distributed codebases is highly valuable
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Familiarity with rigorous code-review practices and software-engineering standards
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Strong written and verbal communication skills
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High attention to technical detail and reproducibility
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Experience with modern AI or machine-learning systems is beneficial but not required
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Prior AI-training or model-evaluation experience is not required
Engagement Details
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Part-time independent contractor engagement
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Fully remote
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Compensation: $60–$120/hour
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Expected commitment: approximately 15 hours per week
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Schedule is flexible, including the option to work evenings or weekends
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Compensation is output-based, with payment made for tasks that meet project specifications
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Minimum weekly submission requirements apply
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Work will involve MCP-based reinforcement-learning environments, software-engineering task design, deterministic verification, and golden reference solutions
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The selection process may include screening questions, an approximately 30-minute AI interview, a technical assessment, and hiring-manager review
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Selected professionals should be prepared to begin their first tasks within approximately 24–48 hours of completing onboarding
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Roles are typically filled within approximately 48 hours
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Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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