What does day-to-day life look like?
Design and develop multi-agent benchmark tasks involving:
Planning, scheduling, and resource allocation
Operational decision-making (project management, logistics, incident response, capacity planning)
Create constraint-rich problem statements with multiple interacting variables
Develop verification scripts to evaluate:
Feasibility (all constraints satisfied)
Completeness (all requirements addressed)
Optimality (efficient solutions)
Build decomposition strategies:
Split tasks across specialized sub-agents (resource-based, constraint-based, conflict resolution, optimization)
Model real-world operational scenarios with dependencies, timelines, and resource constraints
Collaborate on improving task quality, coverage, and evaluation rigor
Requirements
5+ years of experience in operations, project management, logistics, or supply chain
Strong ability to formalize constraints, dependencies, and scheduling logic
Proficiency in Python for building verification and validation scripts
Strong structured problem-solving and decomposition skills
Clear and precise technical writing skills
Experience with AI coding benchmarks (e.g., SWE-bench, Terminal-bench)
Hands-on experience with Docker (Dockerfiles, image builds, debugging)
Requirements
Experience with optimization techniques (linear programming, constraint satisfaction, scheduling algorithms)
Background in operations research
Experience with simulation or modeling tools
Knowledge of AI planning systems or automated reasoning
Project management experience or certifications (PMP, Agile, etc.)
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