Site Automation Engineer - Night Shift
Bright Machines
Job Description
Job Description
RETHINK MANUFACTURING
The only way to ignite change is to build the best team. At Bright Machines®, we’re innovators and experts in our craft who have joined together to manufacture the AI and data center infrastructure at the edge. We believe unifying software, intelligent automation, and data is the answer to delivering quality and flexibility at scale. We deliver products to meet the demands of today while continuously investing in our Bright Factory model to take advantage of what comes next.
Working with us means you’ll have the opportunity to make lasting, impactful changes for our company and our customers. If you’re ready to apply your exceptional skills to a brighter way of manufacturing AI infrastructure, we’d love to speak with you.
ABOUT THE ROLE
The Site Automation Engineer owns the performance and reliability of robotic assembly systems deployed at a major customer site. This role serves as the primary technical interface between the customer, manufacturing partners, field teams, and Bright Machines’ remote experts. You’ll use live data, diagnostic tools, and hands-on automation and robotics troubleshooting to resolve hardware and software issues, drive continuous improvement, and ensure high system uptime. Strong communication, customer focus, and experience in automated manufacturing environments are key to success.
This role supports a 24/7 manufacturing site, with scheduled overnight shifts. To support work-life balance, shifts rotate weekly—three shifts one week and four shifts the next.
WHAT YOU WILL BE DOING- You will be responsible for multiple robotic assembly systems deployed to a major tech customer
- You will be interacting with customer and customer manufacturing partner about performance of our equipment
- You will be collecting customer feedback and sharing it within our organization as part of continuous improvement process and product roadmap development
- You will be the primary interface between a team of remote technical experts and those on the line which includes field service engineers and customer production leads
- Use your troubleshooting skills, live data, diagnostic tools, and customer feedback to assess hardware and software anomalies and determine corrective actions
- Maintain status reports at various levels of detail and synthesis
- Educate and train customers on device operation, maintenance, troubleshooting and repair
- Provide excellent customer service, actively listen to customer concerns, and address issues
- Travel up to 10%, mostly for training
- Experience in an automation and robotics environment
- Bachelor’s Degree (Mechanical or Electrical Engineering); Associate degree with equivalent years of experience may be considered.
- Automation, robotics, and PLC experience
- Understanding of Recipe Debug
- Experience using Vision systems for inspection and point of interest interpolation
- Confidence around electro-mechanical systems and a zest for diagnosing new systems with complex failure modes
- Technical documentation experience (reading, creating, editing)
- Ability to diagnose and repair complex mechanical systems
- Capable of following electrical and mechanical drawings
- Self-starter with ability to work productively with minimal supervision
- Calm, collected demeanor and commitment to customer service
- Experience in an electronics manufacturing environment or similar
- Familiarity with code, command line interfaces, and can find your way around a LAN. (Production-style coding is not required)
BE EMPOWERED TO CHANGE AN INDUSTRY
Bright Machines is a next-generation, AI-enabled manufacturer focused on data center infrastructure production. Bright Machines uses its proprietary AI-based robotics and software to assemble AI infrastructure hardware products (i.e., data center servers) for hyperscalers, neoclouds, and leading Original Equipment Manufacturers (OEMs) to reduce their time to revenue. With its Bright Factory model, Bright Machines builds higher quality data center infrastructure at scale, addresses increasing market demands for computing power due to the surge of AI, and answers the call to the U.S. national mandate to reshore manufacturing.
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