MCP Software Evaluation Environment Author
Job Description
IXO is engaging specialists to evaluate coding benchmarks that require an agent to discover and use MCP-connected information. Your contribution is technical work: make the reasoning inspectable, identify substantive errors and provide evidence that supports a reliable assessment.
Work you will do
• Design repository problems involving bugs, features, refactoring or optimization where relevant context comes from real MCP servers.
• Build the reproducible environment and a golden reference solution, including the tool interactions needed to solve the task.
• Implement deterministic validation that measures both software correctness and appropriate MCP use, and document the important edge cases.
Required background and routes
• Proficiency in at least one of Rust, TypeScript, Go, Java, Python or C++, supported by algorithms/data structures, debugging and performance reasoning.
• Deliver maintainable features, refactor code and improve scalability; communicate technical details precisely and collaborate across disciplines.
Preferred background
• Large distributed repositories, rigorous code-review practice or familiarity with ML/AI systems; prior AI experience is optional.
Deliverables
Submit the completed technical artifact or assessment with its supporting evidence, explicit assumptions, reproducible checks where applicable, and concise reasons for each material judgment. Address review findings within the agreed scope.
Location and schedule
Remote assignments are scheduled by agreement, with no guaranteed weekly volume. Availability planning can include 15 hours per week depending on the track. IXO confirms the applicable timing before work.
Pay and working terms
Per completed task; fee agreed before work USD. Payment is for a completed task that meets the agreed acceptance criteria. The fee, task specification and revision requirements are agreed before work; an advertised time estimate does not determine payment. Applying does not guarantee an assignment. Use public, licensed or otherwise authorized material only; do not submit confidential employer information, personal data or restricted research.