Digital Automation Technology Lead

Requirements

• Degree in Engineering, Computer Science, Automation, Robotics, or related discipline.
• Demonstrated experience in automation engineering projects, OT/IT integration, and relevant data capture platforms (e.g., TetraScience, Zontal).
• Strong hands-on knowledge in Python and at least one of the following: workflow orchestration and orchestration platforms, instrument integration, PLC/SCADA, data pipeline tooling.
• Understanding of AI/ML concepts and practical experience applying them to process or lab automation.
• Experience designing systems where multiple autonomous components coordinate goals.
• Understanding of E2E process workflows in R&D, manufacturing, or process development environments.
• Proven ability to work in a matrixed, hub & spoke, or centre-of-excellence model across global teams.
• Desirable skills and experience
• Experience with agent frameworks (e.g., LangChain/LangGraph, AutoGen, CrewAI, or custom orchestration).
• Exposure to self-driving lab concepts, closed-loop experimentation, or autonomous research platforms (orchestration capabilities).
• Experience with IoT platforms, edge computing, or historian systems (e.g., OSIsoft PI, Aveva).
• Knowledge of robotic process automation.
• Familiarity with digital twins and simulation-driven optimization.
• Knowledge of GxP, data integrity, and compliance in regulated environments.
• Experience in Life Sciences, Crop Protection, or Chemical/Pharma R&D settings.
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Benefits

Additional Information

We have an exciting opportunity for a Digital Automation Technology Lead to drive the convergence of traditional automation, data technologies, and AI agent orchestration to enable self-driving lab environments and autonomous E2E workflows globally as part of our Digital Automation & Process Innovation team. Within the role you will support new R&D centers projects as a point of reference for data-focused automation technology topics. You will translate standards and architectures into scalable, locally deployed solutions while pioneering new paradigms where AI agents coordinate instruments, interpret results, and autonomously drive experimental and operational workflows. Key responsibilities will include: Architecting and implementing the automation backbone for self-driving lab capabilities - closed-loop systems where AI agents plan experiments, trigger instruments, capture data, interpret results, and iterate without manual intervention. Collaborating with scientists and R&D teams to identify high-value workflows suitable for autonomous operation and progressive levels of self-driving maturity. Acting as the primary point of contact, while owning the local relationship with scientists, lab managers, and process engineers to ensure data-driven automation needs are captured, prioritised, and addressed in alignment with the global hub. Owning the end-to-end delivery of high-complexity global initiatives, taking full accountability for technical decision-making and outcomes and cross-functional guidelines to ensure best practice and compliance with Digital Automation & IoT principles. Lead PoC and prototyping initiatives to evaluate innovative solutions (e.g., image processing, OT/IIoT, lab & pilot plant data orchestration). Co-owning the technical roadmap, or components thereof, for digital automation R&D capabilities - i.e., data capture automation, workflow automation, and hyperautomation. Driving the implementation of prioritised digital and data automation projects that drive standardisation to enable FAIR data practices and have positive impact on cross-functional effectiveness & productivity. Representing R&D in complex, strategic initiatives, collaborating effectively across regions and with external stakeholders to ensure solutions are strategically aligned and technically robust, while partnering with data scientists, AI/ML engineers, and IT platform teams to ensure cohesive and strategic solution delivery. Contributing to the Digital Automation technology strategic roadmap with a forward-looking view on core capabilities by providing expertise and technical leadership to the global R&D community. Supporting capability building across local teams on agent-augmented automation, prompt engineering for orchestration, and self-driving lab concepts.

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Company Intel

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