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# Manufacturing Systems Engineer

- **Company:** Titan, LLC
- **Location:** Lumberton, NC, United States
- **Salary:** $70,000 - $85,000
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Databases, Systems Analysis, Python (Programming Language), Microsoft SQL Server, SQL Databases, Transact-SQL, Web Applications, Flask (Web Framework), Large Language Models, Backend, Agentic-AI, Build Management, Information Technology
- **Published:** October 12, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=34811bad844851e6

## About the Role

We are looking for a polymath. The right person is comfortable on the shop floor and in a code editor and doesn't think of those as two different jobs., * Strong systems analysis background.

 * Understands how to document system requirements.
 * Working knowledge of manufacturing operations: work orders, routings, BOMs, scheduling, etc.
 * Working knowledge of inventory control: min/max and reorder logic, ABC classification, cycle counting
 * Solid understanding of Python and SQL.
 * Can take a vague operational problem, ask the right questions, and come back with a working prototype
 * Clear writing - you will document logic and explain decisions to non-technical people

What sets a candidate apart

 * A degree or coursework in manufacturing systems, industrial engineering, operations management, or computer science (any one of these; none is required)
 * Experience with an ERP's database, not just its screens
 * Hands-on work with LLM APIs or agent frameworks such as LangGraph
 * Familiarity with production planning methods: capacity planning, MRP logic, demonstrated-capacity measurement
 * You have read a shop traveler and a stack trace in the same afternoon and were fine with both

## Description

* Design and build web applications in Python (Flask and Anvil) against a SQL Server backend, with T-SQL doing real work in the database
 * Write and tune the planning logic - min/max calculations, demand classification, capacity load, transfer rules
 * Integrate with our ERP: pull orders, inventory, and shipments; push back plans and decisions
 * Build and supervise AI agents that act as production controllers
 * Sit with Production Control and Sales to learn how the work flows, then turn that into requirements and code
 * Test against real plant data, roll out in shadow mode, and own what you ship
 * Document the logic so the next person can read it