Lead AI Engineer - Digital Service Solutions

Business Unit Service delivers advanced digital and outcome-based service solutions worldwide, focusing on next-generation digital service solutions leveraging IoT, cloud platforms, data, and AI for energy and industrial domains.

• University degree (Bachelor’s or Master’s) in Computer Science, Data Science, Engineering, or related technical field
• Proven experience designing, implementing, or governing applied AI/ML solutions in industrial, IoT, or service-oriented environments
• Strong understanding of end-to-end AI pipelines including data preparation, model development, deployment, and monitoring
• Experience integrating AI into enterprise-scale digital solutions using cloud platforms, microservices, and MLOps practices
• Ability to translate AI techniques into operationally relevant outcomes aligned with service and domain needs
• Experience working in cross-functional environments across R&D, engineering, service, and digital organizations
• Strong communication skills and ability to influence architecture and solution decisions across stakeholders
• Experience with LLM-based systems, agentic AI, or advanced analytics platforms is an advantage
• Familiarity with AI governance, ethics, compliance, and regulated industrial environments is meriting

• Define and own the AI R&D capability strategy and architecture for digital service solutions, including applied machine learning, advanced analytics, and LLM-based and agentic AI systems
• Establish architectural principles and standards aligned with cloud-native delivery, industrial scalability, and long-lifecycle service solutions
• Translate service and domain needs into AI models, use cases, and solution-level designs embedded in workflows and decision processes
• Design and govern AI model lifecycles including problem framing, validation, deployment, monitoring, and controlled evolution
• Ensure AI outputs are actionable, interpretable, and aligned with operational and business objectives
• Lead design and governance of agentic AI workflows combining reasoning, orchestration, and automation across service operations
• Collaborate with data platform, digital platform, and IT teams to support AI solutions with scalable data pipelines, feature management, and analytics services
• Establish principles and controls for AI quality, explainability, bias mitigation, and ethical use complying with regulatory and industrial requirements
• Contribute to AI portfolio alignment, reuse, and standardization across solutions to reduce fragmentation and accelerate value
• Act as technical authority and trusted advisor supporting architecture decisions and capability development across Service R&D