Think:

bots that monitor email and alert the right people, scripts that pull data from 5 systems and generate a daily report, AI that reads supplier documents and flags problems automatically. What You'll Do Build and maintain AI agents and automation workflows (Python, LLM APIs) Integrate with business systems — Microsoft Graph, SharePoint, ERP, CMMS, 3PL platforms Parse and analyze documents (PDFs, spreadsheets, COAs) programmatically Write reliable, deterministic scripts for daily operational tasks Monitor, debug, and improve existing automation infrastructure Work with production and operations teams to understand real workflows and pain points Own projects end-to-end — from \"here's the problem\" to \"here's the working solution\"

What We're Looking For Must-haves:

Strong Python skills — you've built things, not just completed tutorials Experience with REST APIs and data integration Comfort with the command line, SSH, basic server administration Familiarity with LLM APIs (OpenAI, Anthropic, or similar) Self-starter mentality — you figure things out before asking for help Clear communication — you can explain what you built and why

Nice-to-haves:

Experience with Microsoft Graph API or Office 365 automation PDF parsing, data extraction, or document processing Basic cloud infrastructure (Linux servers, cron jobs, networking) GitHub portfolio with real projects Interest in manufacturing, operations, or supply chain Why This Role Is Different You won't be writing reports nobody reads or building demos that never ship. Everything you build goes into production and gets used by the CEO, VP of Operations, and floor managers the same week. You'll have direct access to leadership and real autonomy to solve problems your way. We're a small, fast-moving team. If you want bureaucracy and Jira tickets, this isn't it. If you want to build things that matter and learn fast, let's talk.

Pay:

$25.00 - $35.00 per hour Application Question(s): Describe something you automated that wasn't a school assignment. What was the problem, what did you build, and what broke along the way? You're given a supplier PDF with lab results in a table. How would you extract that data programmatically and flag anything out of spec? Walk me through your approach. You deploy a script that runs every morning at 6 AM. Monday morning it didn't run. How do you figure out what happened? You need to pull data from three different APIs, combine it into one report, and email it to the CEO daily. One of those APIs goes down randomly. How do you handle that? What's the last rabbit hole you went down learning something technical — not for school or work, just because you wanted to figure it out? Have you used Claude, ChatGPT, or any other AI assistant to actually build something — not just ask it questions? Tell me what you built and how you used it as a tool

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