Head of Asset Management & AI Transformation

OverviewHead of Asset Management & AI Transformation Remote | Global Role | Multi-Industry This is not a traditional asset management role. This role is designed for someone who understands that the future of maintenance and asset management is driven by data, reliability engineering, and intelligent systems.About MaxAccelerate Technology GroupMaxAccelerate Technology Group is a global technology and transformation business focused on helping asset-intensive organisations improve performance, reduce cost, and scale operations through data, systems, and AI. Through our ecosystem, including DataMax AI, we work with organisations across Facilities Management, Transportation, Pharma, Manufacturing, Energy, and Infrastructure to transform how assets are managed.Our approach is grounded in real operational understanding: Maintenance strategies must be structured, measurable, and optimised. Systems such as IBM Maximo and other EAM platforms must deliver actionable insight. AI must be applied in a way that drives tangible outcomes across cost, labour, and asset performance.The RoleWe are seeking a Head of Asset Management & AI Transformation to lead the definition and delivery of AI-driven asset management solutions. The focus of the role is to take deep operational knowledge — including: RCM frameworks, preventive and condition-based maintenance strategies, workforce planning and labour models, spare parts, inventory, and asset lifecycle considerations and translate these into structured AI use cases and scalable solutions.Key ResponsibilitiesWork closely with Heads of Maintenance, Engineering Leaders, and Operations teams to understand:Maintenance strategies and maturityPreventive vs reactive ratiosLabour utilisation and workforce efficiencySpare parts management and inventory controlDefine and structure AI use cases that address:Reduction in reactive maintenanceOptimisation of preventive maintenance schedulesLabour efficiency and workforce planningSpare parts forecasting and cost reductionAsset lifecycle optimisationDevelop and lead Proof of Concepts (PoCs) that validate:Operational improvementsCost savingsPerformance upliftTranslate business requirements into clear scope of works for DataMax AI R&D teams.Ensure AI solutions integrate effectively with EAM/CMMS platforms (Maximo preferred) and align with real operational workflows.Build clear ROI models, ensuring every solution delivers measurable impact across:Maintenance costsAsset uptimeLabour efficiencyInventory and working capitalSupport clients in adopting solutions that improve their infrastructure, operations, and long-term asset strategy.Why This Role MattersMost organisations have:Maintenance strategies defined on paperSystems implemented but underutilisedData available but not fully leveragedYou will ensure that:Maintenance frameworks such as RCM are not just theoretical, but digitised and optimisedPreventive strategies are continuously refined based on real performance dataLabour and cost structures are aligned with actual operational demandAI is applied in a way that improves real infrastructure outcomes, not just reportingWhat We Are Looking ForStrong background in Asset Management, Maintenance, or Engineering leadership.Deep understanding of:RCM and reliability frameworksPreventive and predictive maintenance strategiesWorkforce and labour optimisationSpare parts and inventory managementExperience working with EAM/CMMS platforms, ideally IBM Maximo.Ability to translate operational challenges into structured, solution-driven approaches.Commercial awareness and the ability to link technical improvements to cost and performance outcomes.The OpportunityDefine how AI is applied to asset management in real environments.Deliver measurable improvements in cost, performance, and efficiency.Shape solutions that can be scaled across multiple industries.ApplyApply if you are interested in moving beyond traditional asset management roles and want to be involved in shaping the next generation of maintenance and asset optimisation. We would welcome a conversation.#J-18808-Ljbffr