Remote AI Supply Chain Task Design - Work Anywhere — Columbus
Traveler-Friendly Insight
Location Flexibility: This role is listed as open to anyone in the world, making it one of the most location-independent engagements available. It is a task-based contract — meaning you pick up and complete discrete tasks on your own schedule, with no fixed office hours or timezone requirements stated. This is as async-friendly as it gets.
Schedule & Workflow: Each task takes approximately 60–75 minutes. You can batch tasks around your travel schedule, work from a café in Lisbon or a co-working space in Chiang Mai, and submit whenever connectivity allows. There is no mention of required live meetings or synchronous standups.
Visa Considerations: Since compensation is per-task (freelance/contractor model), this fits cleanly within most digital nomad visa frameworks — including Portugal's D8, Thailand's LTR, and Colombia's digital nomad visa — as freelance remote income. Always verify local tax obligations.
Earning Context: No per-task rate is disclosed, but as a specialist AI training contract through Toptal, rates tend to be competitive. Even modest per-task pay adds up quickly at 60–75 min/task:
- Lisbon, Portugal: ~€1,800–2,500/month comfortable living — a moderate task volume could cover this.
- Bangkok, Thailand: ~$1,200–1,800/month — very achievable as a side or supplemental income stream.
- Medellín, Colombia: ~$1,000–1,500/month — low barrier to sustain a nomad lifestyle here.
No equipment stipend, coworking allowance, or travel perks are mentioned. This is a lean contractor engagement, best suited as a supplement to existing remote income or during a slower travel period.
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 (e.g., 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.
Required 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.
- Work must have been performed within the last 3 years; must be able to 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 experience with 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.
Engagement Process
- Task-based engagement paid per task, with each task taking approximately 60 to 75 minutes.
- Vetting task instead of a live interview.
- Tasks are reviewed by the client before approval.
Frequently Asked Questions
Is this a fully remote role or is there an office requirement?
How does the task-based compensation model work?
Do I need active, recent supply chain experience to qualify?
Is Python experience mandatory?
When does this engagement start?
