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Automation Engineer, Blades and Vanes Foundry

Job in Bastrop, Bastrop County, Texas, 78602, USA
Listing for: Latent AI
Full Time position
Listed on 2026-05-28
Job specializations:
  • Engineering
    Electrical Engineering, Automation Engineering, Systems Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

AUTOMATION ENGINEER, BLADES AND VANES FOUNDRY

Space

X was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today Space

X is actively developing the technologies to make this possible, with the ultimate goal of enabling human life on Mars.

Power generation poses a key challenge that could slow the worldwide adoption of AI. The Blades and Vanes Investment Casting Manufacturing Team produces components for power generation using investment casting to create equiaxed, directionally solidified, and single‑crystal components that excel under the most demanding operating conditions. As an automation engineer at Space

X, you will apply first principles thinking to design, develop, and maintain core control systems at the cutting edge of investment casting and other manufacturing processes. This includes integrating PLC/SCADA with advanced manufacturing and energy systems for physics‑driven optimization of production processes, as well as developing scalable systems for functionality enhancements, quality inspection, and real‑time process optimization.

RESPONSIBILITIES
  • Integrate electromechanical and mechatronic systems with critical investment casting equipment, including wax injectors, ceramic injectors, preheating, melting, and controlled solidification furnaces
  • Design and develop manufacturing data systems from concept to production, analyzing equipment KPI trends, conducting reliability analysis to create scalable systems for production output, quality inspection, real‑time process optimization, and maintenance strategies to enhance equipment uptime and reliability
  • Implement solutions for data collection/storage, using Python/SQL to interface with MES and production databases, while incorporating sensor data for real‑time condition monitoring and fault prediction
  • Create and optimize HMI/SCADA/MES interfaces; conduct in‑house technology exploration; and integrate predictive analytics for equipment health monitoring
  • Participate in initial equipment conceptual development and carefully balance product specifications, process requirements, layout complexity, cost, and lead‑time limits
  • Lay out new industrial electrical control panels that are NFPA
    79/NEC/UL508A compliant and create electrical, pneumatic, and fluid schematics
  • Architect, write, and debug PLC code, emphasizing generating organized, structured, documented, maintainable, and reusable code for manufacturing applications
  • Implement (ANSI/RIA
    15.06/OSHA compliant) control reliable safety systems for safeguarding robots, gantries, conveyors, and other manufacturing equipment
  • Select and size electrical and electromechanical components such as servo motors and controllers
  • Manage electrical cabinet builds, field wiring, pneumatic, and fluid plumbing
BASIC QUALIFICATIONS
  • Bachelor's degree in an engineering, physics, or computer science discipline
  • 1+ years of experience in the design and commissioning of automation and control systems for industrial applications
PREFERRED SKILLS AND EXPERIENCE
  • Proficiency in industrial systems, including configuring control networks (Ethernet/IP, PROFINET, BACnet, Serial Communication)
  • Experience with multiple PLC systems (Siemens, Allen‑Bradley, Beckhoff, etc.)
  • Experience with programming ABB mechatronic systems
  • Experience with electrical schematics using ePLAN for circuits and power distribution
  • Exposure to a wide variety of production machinery, industrial sensors, and equipment (vision systems, dispense systems, temperature controllers, laser distance sensors, Nut‑Runners, etc.)
  • Hands‑on experience in manufacturing settings, solving complex problems using data and customized solutions. Proven results that have improved equipment reliability and reduced downtime
  • Proficiency in Python and SQL, with experience applying these to analyze sensor data for equipment reliability analysis and predictive modeling
  • Hands‑on experience troubleshooting and fixing electro‑mechanical devices, using hand tools, diagnostic tools (e.g., multimeters, vibration analyzers), and techniques for condition‑based monitoring
  • Proven interpersonal skills and ability to objectively…
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