Toptal
Operations Expert with Python for AI Supply Chain Task Design
Remote, US
Role snapshot
Toptal is hiring a Operations Expert with Python for AI Supply Chain Task Design on a full-time basis. This is a remote role open to candidates in US. The listing highlights Docker, Git, Inventory Management, Supply Chain and Microsoft Excel.
- Company
- Toptal
- Location
- Remote, US
- Work mode
- Remote
- Job type
- Full-time
- Experience
- 5+ years
- Posted
- Nov 5, 2026
Who this role suits
Practitioners with a few years behind them who can work independently, make trade-offs and help newer teammates.
How to prepare your application
- Check your résumé against the listed skills (Docker, Git and Inventory Management) and give each one a concrete example: what you built or achieved, not just that you used it.
- Prepare examples of decisions you drove, how you measured the result, and how you worked with other teams.
- Be ready to discuss trade-offs and scope, not only the tools you have used.
- Read what Toptal publishes about its product or team, so you can say clearly why this role and this company.
- For remote roles, show that you communicate clearly in writing and can work without close supervision.
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About the role
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
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