Operational Technology Engineer

InspireXT•Dallas, TX

17h•Remote

About The Position

We are looking for a hands-on Operational Technology (OT) & Application Engineer to drive industrial data integration initiatives within the Connected Shopfloor proposition. This role sits at the intersection of shopfloor systems and enterprise platforms, enabling real-time data flow from industrial assets to analytics and execution layers using the Litmus Edge suite. You will work directly with shopfloor equipment, connecting heterogeneous machines and transforming raw industrial data into clean, structured data streams that support operational decisions, analytics, and workflow execution. This is a dynamic, technical role that bridges the gap between OT and IT, combining hands-on implementation with customer interaction across Proof of Concept (PoC) and production environments.

Requirements

Bachelor’s degree in Electrical, Electronics, Instrumentation, Mechatronics, Computer Science, or a related field.
Hands-on exposure to industrial or manufacturing environments.
Understanding of PLCs, industrial control systems, sensors, and shopfloor operations.
Familiarity with industrial communication protocols (e.g., OPC-UA, Modbus, MQTT).
Basic programming or scripting knowledge (Python, JavaScript, SQL, or similar).
Strong problem-solving skills and ability to work across OT and IT environments.
Effective communication skills to interact with both technical and non-technical stakeholders.
Willingness to travel to client sites and work in plant environments.

Nice To Haves

Experience with IIoT platforms such as Litmus, Ignition, or Kepware.
Familiarity with cloud platforms (AWS, Azure, GCP) and data integration pipelines.
Understanding of Linux systems and networking fundamentals.
Exposure to containerization or edge deployments (Docker, Kubernetes).
Understanding of APIs, databases, and automated data workflows.
Prior customer-facing or implementation experience in industrial environments.

Responsibilities

Connect and integrate shopfloor machines, PLCs, and sensors across mixed industrial environments using Litmus and related IIoT platforms.
Configure and manage industrial communication protocols including OPC-UA, Modbus, MQTT, and other relevant standards.
Perform data mapping, normalization, and tagging to build structured and contextualised industrial data models (asset hierarchies, tag structures).
Deploy, configure, and maintain Litmus Edge and Litmus Edge Manager across PoC and production environments.
Prepare and hand off clean, reliable data streams for downstream analytics and enterprise execution layers (e.g., Databricks, Oracle Smart Operations).
Diagnose and resolve issues related to connectivity, data quality, and system performance in real-time industrial environments.
Conduct early-stage data quality checks to ensure reliable and usable data pipelines.
Work closely with operators, maintenance engineers, and supervisors to understand real-world shopfloor operations and design practical solutions.
Support condition-based and predictive maintenance use cases from initial data capture through to implementation.
Travel to client sites to implement, validate, and optimise solutions in real manufacturing environments.
Document implementations, configurations, and best practices to ensure client teams can sustain solutions post-deployment.
Support pre-sales activities by validating technical requirements, building demonstrations, and contributing to solution discussions where required.
Assist in RFI/RFP responses by providing technical inputs and solution configurations.
Support post-sales implementation and provide technical assistance, including structured handovers and issue resolution.
Collaborate with partners and internal teams to deliver solution architectures and technical guidance.
Contribute to reusable assets, processes, and knowledge bases (including use of NaturalAI™).
Provide feedback on product performance, customer requirements, and integration challenges.
Stay updated on IIoT platforms, manufacturing trends, and relevant technologies.
Identify opportunities for improving solution delivery, data quality, and shopfloor integration practices.