Manufacturing Software Engineer

The Manufacturing Software team builds the systems that keep the Georgetown facility running, including equipment management, real-time process data, quality alerts, and the dashboards operators and engineers rely on throughout every shift. This software operates directly on the factory floor, shaping real-time decisions and directly influencing the metrics that matter most: throughput, yield, and uptime.

This role owns that scope end to end, from the APIs and data pipelines that bring information off the line, to the web applications Process Engineering and Equipment Engineering use to configure alerts and monitor performance in real time. The ideal candidate delivers quickly, navigates ambiguity effectively, and works closely with the engineers who depend on this software every day.

This is not a typical enterprise software role. It is the software backbone of how Cel Link manufactures flexible circuits at scale, and this work will directly shape how efficiently and reliably that manufacturing operates.

• Design, develop, and deploy full-stack manufacturing applications using modern front-end frameworks (React) and scalable back-end services that support factory operations.
• Build and maintain real-time manufacturing systems and dashboards for SPC, OEE, throughput, availability, yield, and quality, including configurable alerts and proactive monitoring.
• Architect APIs, data models, and event-driven systems that integrate factory equipment, PLCs, sensors, computer vision systems, MES platforms, and other business systems.
• Develop real-time data pipelines using streaming technologies such as Kafka, MQTT, Web Sockets, REST, and gRPC to transform machine and process data into actionable operational insights.
• Partner with Controls, Process, Equipment, Manufacturing, and Quality Engineering teams to define data requirements, integrate new equipment, and validate manufacturing data flows.
• Design and implement validation, testing, and observability solutions to ensure production systems, equipment integrations, and data pipelines operate reliably and accurately.
• Lead projects from requirements gathering and solution architecture through implementation, deployment, support, and continuous improvement.
• Troubleshoot and resolve issues across software, infrastructure, machine, and PLC layers to minimize downtime and improve manufacturing performance.
• Develop automation, predictive maintenance, anomaly detection, computer vision, and AI-driven solutions that improve throughput, yield, uptime, and engineering productivity.
• Evaluate and deploy emerging manufacturing technologies, including AI agents, LLM workflows, edge AI, and digital twin technologies to drive operational excellence.
• Establish engineering standards, documentation, code quality practices, and scalable operational processes for manufacturing software systems.
• Collaborate closely with factory operations and plant leadership to rapidly deliver solutions that solve real-world manufacturing challenges.

• Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, Mechatronics, or equivalent practical experience.
• 3+ years of professional software engineering experience building and supporting production systems.
• Strong programming skills in one or more of the following:
  Go, Python, C#, Type Script, or Java, with the ability to learn new technologies quickly.
• Experience developing and owning full-stack applications, including modern web front ends, back-end services, APIs, and databases.
• Experience with industrial automation environments, including PLCs, control systems, equipment integration, and machine data collection through APIs, MQTT, or similar technologies.
• Experience designing real-time, event-driven, or distributed systems, including data pipelines, streaming architectures, and scalable software solutions.
• Strong database and data architecture skills across relational and high-performance data platforms.
• Proficiency in modern software engineering practices, including source control, code reviews, CI/CD, testing, monitoring, and observability.
• Comfortable working in manufacturing environments and troubleshooting issues across software, equipment, and factory operations.
• Self-driven communicator who can lead projects independently and collaborate effectively across engineering, operations, and manufacturing teams.

• Manufacturing, automotive, or industrial software experience.
• Knowledge of SPC, quality systems, and manufacturing analytics.
• Experience with streaming architectures, real-time data systems, and time-series visualization tools.
• Experience with AI/ML technologies including LLMs, computer vision, anomaly detection, and predictive maintenance.
• Exposure to cloud-native platforms, containerization, CI/CD, edge computing, or digital twin technologies.

Salaried; exempt; available/willing to work overtime to meet…