Operations Expert with Python for AI Supply Chain Task Design

Free resume; Belgique; Remote; EUR 96,000 - 138,000; Full time

Job summary

Toptal is seeking an Operations Expert with Python to design AI-driven Terminal-Bench tasks for supply chain benchmarking. You’ll turn real planning work into end-to-end challenges with files, a working solution, and automated correctness checks.

This remote, task-based role requires hands-on supply chain planning experience, Python fluency, and familiarity with ERP/WMS data exports. Compensation is per task and performance-based.

Qualifications

• 3+ years hands-on supply chain or production planning work.
• Experience with ERP/WMS data exports and reports.
• Proficient in Python and command-line tools.
• Able to design end-to-end tasks with rules and tests.
• Available to start around November 4, 2026.

Responsibilities

• Design expert-level Terminal-Bench tasks by turning a real supply chain task into a challenge an AI agent solves end to end.
• Define the files, data exports and systems each task runs on (ERP, MES, WMS) to reflect realistic planning conditions.
• Write a working solution for each task (e.g., a 5-day production plan) and ensure it can be solved in 60–75 minutes.
• Build automated checks to prove correctness using tests or scripts that accept valid answers and catch planning errors.
• Document the rules, constraints and SOPs that decide each case, including edge cases and data inconsistencies.
• Iterate on tasks based on reviewer feedback, keeping instructions unambiguous and reproducible in a CLI environment.

Skills

Python

Command line

Supply chain planning

ERP/WMS familiarity

CSV/JSON handling

Tools

ERP systems

WMS data exports

CSV/JSON

Job description

Operations Expert with Python for AI Supply Chain Task Design

Toptal · Anywhere in the World, Belgium · Posted 3d ago

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Job Description

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