End-to-End Technical Leader - System.AI (M/F)

Join Schneider Electric and help transform critical infrastructure through AI and data-driven services.

At Schneider Electric, we leverage Artificial Intelligence, advanced analytics, and Condition-Based Maintenance to improve the performance, resilience, and sustainability of critical infrastructure.

Within System.AI, our global Center of Excellence, you will join a rapidly growing team developing and deploying Data & AI solutions for Data Centers, industrial environments, healthcare facilities, electrical distribution networks, and microgrids. You will help turn innovative concepts into scalable, industrialized solutions that deliver measurable value to our customers.

Your Role

As an End-to-End Technical Leader, you are responsible for the technical consistency of System.AI solutions throughout their lifecycle, from opportunity qualification to deployment and operational handover.

Working at the intersection of Sales, Architecture, Engineering, Data & AI teams, and Delivery organizations, you ensure solutions are technically sound, executable, secure, and aligned with customer business objectives.

You bring an end-to-end perspective that connects customer needs, solution architecture, and delivery constraints, enabling scalable deployment of innovative AI-powered solutions.

Your Missions

End-to-End Technical Ownership

• Own the technical lifecycle of System.AI solutions from opportunity qualification through deployment and operational handover.
• Ensure alignment between customer requirements, target architecture, delivery constraints, and business objectives.
• Act as the primary technical authority for pilot projects and Engineer-to-Order (ETO) solutions.
• Support the industrialization of solutions to enable scalability and repeatability across customers and regions.

• Support Sales teams during technical qualification of opportunities.
• Perform feasibility studies, technical risk assessments, and architecture validation activities.
• Contribute to scope definition, Data & AI architecture design, effort estimation, and technical proposal creation.
• Participate in customer workshops, technical presentations, and bid defense sessions.

• Design and lead solutions covering the complete value chain, from data acquisition and contextualization to analytics and business value generation.
• Ensure reliability, security, and scalability of data pipelines.
• Validate that AI models and analytics capabilities are aligned with operational constraints and business use cases.
• Lead technical decisions related to Edge-to-Cloud architectures, Data Platforms, Azure services, and AVEVA CONNECT environments.
• Ensure delivered solutions generate measurable outcomes in predictive maintenance, asset availability, and operational performance.

• Coordinate engineering, integration, development, and deployment teams.
• Ensure alignment between target architecture, implementation activities, and customer operational requirements.
• Manage technical risks related to architecture, cybersecurity, data quality, and OT/IT integrations.
• Support teams in resolving complex technical challenges related to connectivity, cloud infrastructure, edge computing, and data platforms.
• Ensure deployment readiness, documentation quality, and successful operational handover.
• Capture lessons learned and contribute to the improvement of reusable frameworks, tools, and delivery methodologies.

• Master's degree in Computer Science, Data Engineering, Electrical Engineering, Automation, or a related field.
• Minimum 7 years of experience in technical solution delivery, systems integration, solution architecture, or application engineering.
• Strong experience in IIoT, Cloud platforms, Data Platforms, and Edge-to-Cloud architectures.
• Good understanding of industrial connectivity, DevOps practices, and OT/IT integration challenges.
• Proven experience in customer-facing technical projects.
• Fluent English required; French is a strong asset.

• Strong expertise in IIoT architectures, including OPC-UA, MQTT, Modbus, Edge Computing, industrial gateways, and industrial data acquisition.
• Experience integrating OT systems (SCADA, BMS, DCIM) with Cloud platforms.
• Knowledge of AVEVA CONNECT and industrial data management platforms.
• Experience with Microsoft Azure, cloud-native architectures, microservices, APIs, containers, and Kubernetes.
• Familiarity with DevOps methodologies, CI/CD pipelines, and modern deployment environments.
• Understanding of predictive maintenance, Condition-Based Maintenance (CBM), and asset performance management.
• Knowledge of cybersecurity principles applied to industrial systems and critical infrastructure.
• Strong technical leadership, problem-solving, and stakeholder management capabilities.
• Excellent communication skills in international and multicultural environments.

• Help shape Schneider Electric's next generation of AI-powered services.
• Work on strategic projects supporting Data Centers and critical infrastructure.
• Operate at the intersection of AI, Data, Cloud, IIoT, and Predictive Maintenance.
• Collaborate with world-class experts in architecture, analytics, and industrial systems.
• Contribute directly to the growth of one of Schneider Electric's most innovative business areas.