Remote Operations Analyst – Multi-Agent Benchmark Engineer

About the role

We are looking for a Remote Operations Analyst to design and implement multi-agent benchmark tasks that simulate real-world planning, scheduling and resource-allocation problems. The role is a short-term contract (4 weeks) focused on creating constraint-rich scenarios for AI research and evaluation.

Key responsibilities

• Design and develop multi-agent benchmark tasks covering logistics, project management, incident response and capacity planning.
• Build detailed problem statements with multiple dependencies, variables and resource constraints.
• Write Python scripts to assess feasibility, completeness and optimality of the generated tasks.
• Decompose complex operational problems into structured sub-tasks for multi-agent systems.
• Model scenarios with timelines, dependencies and resource limits, and collaborate with internal teams to improve task quality and evaluation rigor.

Required profile

• Strong experience in operations, project management, logistics or supply-chain environments.
• Deep understanding of constraints, dependencies and scheduling logic.
• Proficiency in Python for validation and verification scripting.
• Excellent technical communication and documentation abilities.

Required skills

• Python programming
• Docker
• Linear programming and other optimization techniques
• Constraint satisfaction and scheduling algorithms
• Experience with AI planning or automated reasoning systems
• Familiarity with AI benchmark suites (e.g., SWE-bench, Terminal-bench)

What we offer

• Competitive hourly rate of $15 USD
• Fully remote work with flexible hours (20-40 h/week)
• Opportunity to contribute to cutting-edge AI benchmarking research