Remote | Senior Software Engineer — $80–$120/hour
Summary
Part-time, fully remote contractor role for senior engineers to design reinforcement-learning environments that evaluate AI systems on realistic software-engineering tasks (bug fixing, feature work, refactoring, performance tuning) with MCP tool integration. Requires strong coding in Python, Java, Rust, C++, Go, or TypeScript; paid $80-$120/hour, output-based.
We are sharing a specialised consulting opportunity for experienced Senior Software Engineers with strong expertise in Python, Java, Rust, C++, Go, TypeScript, algorithms, debugging, feature development, refactoring, performance optimisation, and Model Context Protocol (MCP) tools to contribute to an advanced AI training and reinforcement-learning environment project.
Selected professionals will design reproducible software-engineering environments that test advanced AI systems on realistic coding problems requiring both strong engineering judgement and effective interaction with MCP servers. Tasks may involve debugging, feature development, refactoring, performance optimisation, information discovery, deterministic verification, and golden reference solutions. No prior experience in AI is required.
Key Responsibilities
Engineering Environment & MCP Development
- Design reproducible software-engineering tasks involving debugging, feature development, refactoring, and performance optimisation
- Build scenarios requiring interaction with real MCP servers and external information sources
- Create workflows testing both software-engineering ability and appropriate tool use
- Define clear objectives, expected behaviour, and acceptance criteria
- Analyse unfamiliar codebases, dependencies, and technical environments
Software Engineering & Performance
- Work across C++, Python, Java, Go, TypeScript, Rust, or comparable languages
- Diagnose complex defects and implement maintainable root-cause fixes
- Develop and refactor features while preserving correctness and improving architecture
- Analyse algorithmic and implementation-level performance bottlenecks
- Evaluate maintainability, scalability, latency, throughput, and resource-utilisation trade-offs
Verification & Technical Quality
- Develop deterministic verification mechanisms for each environment
- Create golden reference solutions demonstrating correct task completion
- Ensure tests distinguish correct, incomplete, and incorrect solutions reliably
- Review technical outputs for correctness, maintainability, and appropriate MCP usage
- Document implementation decisions, validation logic, and technical reasoning clearly
Ideal Profile
- Strong professional software-engineering experience
- Proficiency in one or more of C++, Python, Java, Go, TypeScript, or Rust
- Deep understanding of algorithms and data structures
- Strong debugging, feature-development, refactoring, and performance-optimisation skills
- Proven ability to build maintainable and scalable software
- Experience working with large or distributed codebases is highly valuable
- Strong code-review experience and familiarity with software-engineering best practices
- Excellent written and verbal technical communication
- Comfortable collaborating across remote and cross-functional teams
- Familiarity with MCP, AI systems, or machine-learning tooling is advantageous but not required
- No prior AI-training experience is required
Engagement Details
- Part-time independent contractor engagement
- Fully remote
- Expected commitment: approximately 15 hours per week
- Displayed compensation range: $80–$120/hour
- Actual compensation structure is output-based, with payment made per task that meets project specifications
- Task completion time may vary depending on experience and workflow
- Minimum weekly submission requirements apply; the source does not specify the exact number of required tasks
- Work will involve reinforcement-learning environment creation, MCP tool use, debugging, feature implementation, refactoring, performance optimisation, deterministic verification, and golden reference solutions
- Screening may include an approximately 30-minute AI interview and technical assessment
- Roles are typically filled within approximately 48 hours, with initial tasks expected within approximately 24–48 hours after onboarding
- Project scope, workload, technical environments, and evaluation standards may evolve depending on project requirements
- 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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