Overview
A fast-growing AI data company is hiring supply chain practitioners to design expert-level Terminal-Bench tasks for evaluating AI agents. You will turn real planning work into end-to-end challenges, each with files, a working solution and an automated correctness check. The goal is to build a benchmark grounded in real operations work.
THIS IS A TASK BASED COMPENSATION MODEL. PLEASE CHECK THE APPLICATION QUESTIONS FOR MORE DETAILS.
Responsibilities
• Design expert-level Terminal-Bench tasks by turning a real supply chain task from your work into a challenge an AI agent solves end to end.
• Define the files, data exports and systems each task runs on, such as ERP, MES and WMS extracts, so the scenario reflects realistic planning conditions.
• Write a working solution for each task, for example a 5-day production plan, and confirm it can be solved in 60 to 75 minutes.
• Build the automated check that proves the result is correct, using tests or scripts that accept valid answers and catch planning errors objectively.
• Document the written rules, constraints and SOPs that decide each case, along with realistic edge cases, data inconsistencies and common planner errors from your process.
• Iterate on tasks based on reviewer feedback, keeping instructions unambiguous, data consistent and the solution and verification reproducible in a command-line environment.
Skills/Experience
• 3+ years of hands-on supply chain or production planning work (not only studying, selling or managing it), or a PhD with active research in the subfield
• Did the work within the last 3 years and can name the systems, tools, data and rules used
• Personally executed a process where each case is decided by written rules such as SOPs, planning rules or constraints
• Worked inside systems of record (ERP, WMS) and with their exports or reports
• Can describe edge cases, data inconsistencies and common planner errors, and how a mistake would be caught
• Technical fluency in Python or another language and the command line, plus files, CSV/JSON, APIs or databases
• Available to start around November 4, 2026
Nice-to-have
• Automated or audited the process with scripts, SQL, RPA or rules engines
• 5+ years in the same process family
• Docker, Git and experience writing tests
• Hands-on experience with SAP or other ERPs and TMS/WMS platforms
• Advanced Excel skills
Process
• Task-based engagement paid per task, with each task taking about 60 to 75 minutes
• Vetting task instead of a live interview
• Tasks are reviewed by the client before approval

Overview
A fast-growing AI data company is hiring supply chain practitioners to design expert-level Terminal-Bench tasks for evaluating AI agents. You will turn real planning work into end-to-end challenges, each with files, a working solution and an automated correctness check. The goal is to build a benchmark grounded in real operations work.
THIS IS A TASK BASED COMPENSATION MODEL. PLEASE CHECK THE APPLICATION QUESTIONS FOR MORE DETAILS.
Responsibilities
• Design expert-level Terminal-Bench tasks by turning a real supply chain task from your work into a challenge an AI agent solves end to end.
• Define the files, data exports and systems each task runs on, such as ERP, MES and WMS extracts, so the scenario reflects realistic planning conditions.
• Write a working solution for each task, for example a 5-day production plan, and confirm it can be solved in 60 to 75 minutes.
• Build the automated check that proves the result is correct, using tests or scripts that accept valid answers and catch planning errors objectively.
• Document the written rules, constraints and SOPs that decide each case, along with realistic edge cases, data inconsistencies and common planner errors from your process.
• Iterate on tasks based on reviewer feedback, keeping instructions unambiguous, data consistent and the solution and verification reproducible in a command-line environment.
Skills/Experience
• 3+ years of hands-on supply chain or production planning work (not only studying, selling or managing it), or a PhD with active research in the subfield
• Did the work within the last 3 years and can name the systems, tools, data and rules used
• Personally executed a process where each case is decided by written rules such as SOPs, planning rules or constraints
• Worked inside systems of record (ERP, WMS) and with their exports or reports
• Can describe edge cases, data inconsistencies and common planner errors, and how a mistake would be caught
• Technical fluency in Python or another language and the command line, plus files, CSV/JSON, APIs or databases
• Available to start around November 4, 2026
Nice-to-have
• Automated or audited the process with scripts, SQL, RPA or rules engines
• 5+ years in the same process family
• Docker, Git and experience writing tests
• Hands-on experience with SAP or other ERPs and TMS/WMS platforms
• Advanced Excel skills
Process
• Task-based engagement paid per task, with each task taking about 60 to 75 minutes
• Vetting task instead of a live interview
• Tasks are reviewed by the client before approval