Head of Artificial Intelligence
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Key skills for this role
About the Role
Nedra Search is recruiting a Head of AI for a major UAE-based energy and utility organization. This leadership role involves defining and leading the AI agenda, building a team, and delivering AI and digital twin solutions for critical infrastructure.
Key Skills for This Role
Responsibilities
- Define the AI roadmap across generation, transmission/distribution and water assets
- Build, lead and develop a multidisciplinary team of data scientists, simulation engineers and ML engineers
- Serve as the organisation's senior authority on industrial AI, advising executive leadership on opportunities, investments and risks
- Deliver high value AI use cases: predictive maintenance, anomaly detection, energy optimisation, demand forecasting and asset lifecycle management
- Establish MLOps practices to move models from pilot to reliable production at scale
- Ensure AI solutions meet standards for explainability, safety and operational trust in critical infrastructure environments
- Lead the design and deployment of asset, process and system level digital twins across critical infrastructure
- Integrate physics based simulation, real time operational data (SCADA, historians, IoT sensors) and machine learning into unified twin environments
- Partner with OEMs, engineering firms and technology vendors to accelerate delivery while building internal capability
- Shape the industrial data architecture (data historians, time series platforms, cloud/edge infrastructure) required to support AI workloads and Digital Twin Capability
- Champion data quality, governance and interoperability across OT and IT environments
- Collaborate with cybersecurity teams to ensure secure OT/IT integration
Requirements
- 15+ years in industrial digital technology, with 7+ years leading industrial AI, digital twin or advanced analytics programmes
- Track record in the energy, utilities, oil & gas, or heavy industrial sectors
- Proven experience taking industrial AI/twin initiatives from concept to production at scale
- Experience with major industrial platforms (e.g., AVEVA, Bentley, Siemens Xcelerator, GE Vernova, AspenTech, Cognite) and cloud environments (Azure, AWS)
- Strong understanding of physics based modelling, simulation and data driven approaches
- Solid grasp of industrial data landscapes: SCADA, historians (PI/OSIsoft), IoT, edge computing and OT/IT integration
- Working knowledge of modern ML engineering and MLOps practices
- Understanding of cybersecurity considerations in critical infrastructure environments
- Degree in Engineering, Computer Science, Physics or a related field; advanced degree preferred
Full Job Posting
Role Overview
- Role: Head of AI
- Reporting line: CTO
- Sector: Energy / Utilities
- Location: Abu Dhabi, UAE
- We are currently representing a major UAE based energy and utility organisation at the forefront of the region's energy transition in recruiting a Head of AI.
- With large scale operations spanning power generation, water and renewable assets, the organisation is investing significantly in digital technologies with AI capabilities and digital twin at the core of its strategy to optimise asset performance, reliability and sustainability.
- The Head of AI will define and lead the organisation's AI agenda across its asset portfolio.
- This is a build and scale leadership role: establishing the strategy, platform and team to bring physics based and data driven modelling into daily operations from predictive maintenance and process optimisation to energy efficiency and grid intelligence.
- The role works closely with operations, engineering, and asset management leadership.
Key Responsibilities Strategy & Leadership
- Define the AI roadmap across generation, transmission/distribution and water assets
- Build, lead and develop a multidisciplinary team of data scientists, simulation engineers and ML engineers
- Serve as the organisation's senior authority on industrial AI, advising executive leadership on opportunities, investments and risks
Key Responsibilities Applied AI & Digital Twin Delivery
- Deliver high value AI use cases: predictive maintenance, anomaly detection, energy optimisation, demand forecasting and asset lifecycle management
- Establish MLOps practices to move models from pilot to reliable production at scale
- Ensure AI solutions meet standards for explainability, safety and operational trust in critical infrastructure environments.
- Lead the design and deployment of asset, process and system level digital twins across critical infrastructure.
- Integrate physics based simulation, real time operational data (SCADA, historians, IoT sensors) and machine learning into unified twin environments.
- Partner with OEMs, engineering firms and technology vendors to accelerate delivery while building internal capability.
Key Responsibilities Data & Platform Foundations
- Shape the industrial data architecture (data historians, time series platforms, cloud/edge infrastructure) required to support AI workloads and Digital Twin Capability.
- Champion data quality, governance and interoperability across OT and IT environments
- Collaborate with cybersecurity teams to ensure secure OT/IT integration
Key Responsibilities Stakeholder & Value Management
- Build strong partnerships with plant operations, asset management and engineering to drive adoption on the ground
- Define and track the business value of the portfolio: availability gains, cost reduction, efficiency and emissions impact
- Represent the organisation in industry forums and with government stakeholders on digital energy innovation
Experience & Qualification
- 15+ years in industrial digital technology, with 7+ years leading industrial AI, digital twin or advanced analytics programmes
- Track record in the energy, utilities, oil & gas, or heavy industrial sectors ideally spanning both operations facing and technology leadership roles
- Proven experience taking industrial AI/twin initiatives from concept to production at scale
- Experience with major industrial platforms (e.g., AVEVA, Bentley, Siemens Xcelerator, GE Vernova, AspenTech, Cognite) and cloud environments (Azure, AWS)
- Strong understanding of physics based modelling, simulation and data driven approaches and when to use each.
- Solid grasp of industrial data landscapes: SCADA, historians (PI/OSIsoft), IoT, edge computing and OT/IT integration
- Working knowledge of modern ML engineering and MLOps practices
- Understanding of cybersecurity considerations in critical infrastructure environments
- Degree in Engineering, Computer Science, Physics or a related field; advanced degree preferred
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