Custom Software Engineering Lead

What matters most

• IT/OT Convergence Architecture

  The role requires defining reference architectures that bridge operational technology (PLC, DCS, SCADA) with enterprise IT systems. You must demonstrate the ability to design secure, scalable connectivity patterns using protocols like OPC UA, MQTT, and Sparkplug B while adhering to ISA-95 and Purdue model standards.

• Industrial AI and Data Pipeline Design

  You are expected to architect end-to-end data pipelines for time-series and event data, enabling Industrial AI use cases such as predictive maintenance and anomaly detection. This involves contextualizing raw OT data and integrating it with cloud platforms, MES/MOM, and Digital Twin frameworks.

• OT Cybersecurity Governance

  Implementing resilient architectures is a core priority, requiring deep knowledge of IEC 62443 and NIST frameworks. You must be prepared to design secure zones, conduits, and zero-trust remote access solutions to protect critical manufacturing infrastructure.

• Client Engagement and Technical Leadership

  Beyond technical design, you must lead technical workshops, respond to RFPs/RFIs, and manage PoCs. You will act as the bridge between client business objectives and complex technical delivery, requiring strong stakeholder management and the ability to quantify business outcomes.

Likely challenges to think through

• Brownfield Integration Complexity

  Many manufacturing environments involve legacy equipment that lacks modern connectivity. You will likely face challenges in retrofitting these systems without disrupting production. Prepare by discussing your approach to site assessments and how you handle protocol translation and data contextualization in heterogeneous environments.

• Balancing Security with Operational Availability

  Implementing cybersecurity measures like network segmentation can conflict with the high-availability requirements of production lines. Be prepared to explain how you balance strict security controls (IEC 62443) with the need for low-latency, continuous industrial operations.

• Scaling PoCs to Global Rollouts

  Moving from a successful Proof of Concept to a multi-site, scalable deployment is a common hurdle. You may be tested on your ability to create reusable frameworks, manage global team dependencies, and ensure consistent data quality across diverse manufacturing sites.

Topics to prepare

• IT/OT Convergence and ISA-95 Architecture

  Review the Purdue Model and ISA-95 standards to understand how to bridge the gap between operational technology (OT) and enterprise IT systems. Practice mapping data flows from plant-floor PLCs and SCADA systems through to MES/MOM and cloud-based analytics platforms.

• Industrial Cybersecurity Frameworks

  Study the IEC 62443 standard and NIST Cybersecurity Framework in the context of industrial environments. Focus on designing secure zones and conduits, implementing network segmentation, and managing identity and access in brownfield manufacturing sites.

• Unified Namespace (UNS) and Data Contextualization

  Research the concept of a Unified Namespace for industrial data. Prepare to explain how to structure asset hierarchies and semantic models to ensure time-series data from disparate industrial protocols is contextualized for AI and Digital Twin applications.

Skills to revise

• Industrial Connectivity Protocols

  Demonstrate proficiency in configuring and troubleshooting OPC UA, MQTT, and Sparkplug B. Be prepared to discuss how these protocols facilitate real-time data streaming from edge gateways to enterprise data lakes.

• Industrial AI and MLOps

  Practice designing end-to-end pipelines for predictive maintenance and anomaly detection. Focus on the lifecycle of industrial models, including data preparation, edge deployment, and monitoring performance in high-availability manufacturing environments.

• Edge Computing and Containerization

  Review the deployment of containerized workloads using Docker and Kubernetes at the industrial edge. Focus on managing edge-to-cloud integration, ensuring data quality, and maintaining system observability in remote plant locations.

• Develop an IT/OT Convergence Reference Architecture

  Create a visual diagram and supporting documentation demonstrating how you would bridge OT systems (PLC, SCADA, DCS) with enterprise cloud platforms. Ensure your design incorporates ISA-95/Purdue model principles, secure network segmentation, and data contextualization strategies.

• Prepare a Case Study on Industrial Data Pipelines

  Draft a project walkthrough detailing how you designed a data pipeline for a manufacturing environment. Focus on the ingestion of time-series data using protocols like OPC UA or MQTT, the implementation of a Unified Namespace, and how you ensured data quality for downstream Industrial AI applications.

• Formulate an Industrial Cybersecurity Strategy

  Outline your approach to securing a brownfield manufacturing site. Detail how you apply IEC 62443 or NIST frameworks, specifically addressing zone/conduit segmentation, secure remote access, and vulnerability management in an environment with legacy OT assets.

• Draft an MLOps Framework for Edge AI

  Prepare a technical summary explaining your process for deploying and monitoring AI models (e.g., predictive maintenance or anomaly detection) at the edge. Include how you manage containerized workloads using Kubernetes/Docker and how you handle model retraining and performance monitoring.

• Prepare Strategic Questions for Stakeholders

  Develop a list of insightful questions regarding the company's current approach to digital twin maturity, their preferred industrial vendor ecosystems, and how they balance rapid PoC development with long-term architectural governance in global manufacturing rollouts.