SwarmBench Task Engineer – Planning / Operations

About the role

The SwarmBench Task Engineer will design and develop multi-agent benchmark tasks that simulate real-world planning, scheduling and resource allocation challenges. Working remotely, you will create operational scenarios that test the capabilities of AI systems in logistics, project management and incident response.

Key responsibilities

• Design multi-agent benchmark tasks focused on planning, scheduling and resource allocation.
• Create realistic operational scenarios such as logistics, project management, incident response and capacity planning.
• Build constraint-rich problem statements with multiple dependencies and variables.
• Develop Python scripts to evaluate feasibility, completeness and optimality of solutions.
• Decompose complex problems into structured sub-tasks for multi-agent systems.
• Model scenarios with timelines, dependencies and resource constraints.
• Collaborate with cross-functional teams to improve task quality, coverage and evaluation rigor.

Required profile

• Strong experience in operations, project management, logistics or supply chain.
• Deep understanding of constraints, dependencies and scheduling logic.
• Proficiency in Python for validation and verification scripting.
• Excellent structured problem-solving and decomposition abilities.
• Ability to model real-world operational scenarios and document technical solutions.
• Clear technical communication skills and ability to meet tight deadlines.

Required skills

• Python
• Docker
• Linear programming
• Constraint satisfaction
• Scheduling algorithms
• Operations research
• Simulation or modeling tools
• AI planning systems
• AI benchmark experience (e.g., SWE-bench, Terminal-bench)