Head of Asset Management & AI Transformation

Head 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. If your experience is rooted in Reliability-Centred Maintenance (RCM), preventive and predictive strategies, labour optimisation, and cost control, and you are interested in applying this knowledge to AI-driven solutions, this is a unique opportunity to operate at the forefront of the industry. About MaxAccelerate Technology Group MaxAccelerate 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 Role We 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 Responsibilities - Work closely with Heads of Maintenance, Engineering Leaders, and Operations teams to understand: - Maintenance strategies and maturity - Preventive vs reactive ratios - Labour utilisation and workforce efficiency - Spare parts management and inventory control - - Define and structure AI use cases that address: - Reduction in reactive maintenance - Optimisation of preventive maintenance schedules - Labour efficiency and workforce planning - Spare parts forecasting and cost reduction - Asset lifecycle optimisation - - Develop and lead Proof of Concepts (PoCs) that validate: - Operational improvements - Cost savings - Performance uplift - - Translate 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 costs - Asset uptime - Labour efficiency - Inventory and working capital - - Support clients in adopting solutions that improve their infrastructure, operations, and long-term asset strategy Why This Role Matters Most organisations have: - Maintenance strategies defined on paper - Systems implemented but underutilised - Data available but not fully leveraged This role exists to bridge that gap. You will ensure that: - Maintenance frameworks such as RCM are not just theoretical, but digitised and optimised - Preventive strategies are continuously refined based on real performance data - Labour and cost structures are aligned with actual operational demand - AI is applied in a way that improves real infrastructure outcomes, not just reporting What We Are Looking For - Strong background in Asset Management, Maintenance, or Engineering leadership - Deep understanding of: - RCM and reliability frameworks - Preventive and predictive maintenance strategies - Workforce and labour optimisation - Spare parts and inventory management - - Experience 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 Opportunity This role offers the opportunity to work across industries and influence how organisations manage and optimise critical assets. You will play a key role in: - Defining how AI is applied to asset management in real environments - Delivering measurable improvements in cost, performance, and efficiency - Shaping solutions that can be scaled across multiple industries Apply 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.

Strong background in Asset Management, Maintenance, or Engineering leadership. Deep understanding of RCM and reliability frameworks. Preventive and predictive maintenance strategies. Workforce and labour optimisation. Spare parts and inventory management. Experience 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.

Lead the definition and delivery of AI-driven asset management solutions by translating deep operational knowledge (RCM frameworks, preventive and condition-based maintenance, workforce planning, spare parts/inventory, asset lifecycle) into structured AI use cases and scalable solutions. Collaborate with maintenance, engineering, and operations leaders to understand maintenance maturity, labour utilisation, and inventory control. Define and structure AI use cases to reduce reactive maintenance, optimise preventive maintenance schedules, improve labour efficiency, forecast spare parts, and optimise asset lifecycle. Develop and lead PoCs to validate operational improvements, cost savings, and performance uplift. Translate business requirements into scope of works for DataMax AI R&D teams and ensure AI solutions integrate with EAM/CMMS platforms (IBM Maximo preferred). Build ROI models to demonstrate measurable impact across maintenance costs, asset uptime, labour efficiency, and inventory. Support clients in adopting solutions that improve infrastructure, operations, and long-term asset strategy.