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Operations Expert with Python for AI Supply Chain Task Design

Toptal
📍 Anywhere in the World 💰 🕑 Any timezone
Full-time Mid-level Engineering All Other Remote

Job Description

Headquarters:

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

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