ASPIRE Global Service Centre AI and Automation Lead

Role Summary:

Our ASPIRE Global Service Centre is the central hub of our Service Management operations. Beyond a traditional Service Desk, it stands as the central authority and shared service delivery hub, orchestrating all operational workflows, processes, procedures, and tooling. Its a core delivery component of the Version 1 ASPIRE Managed Services offering that places AI, continuous improvement and business innovation at the heart of everything Version 1 does. With a focus on supporting self-service and automation, we utilise the best digital capabilities of the ServiceNow ITSM tooling product to provide the very best Experience to our Customers.

We are seeking an experienced and results-driven AI and Automation Lead who will be responsible for driving the strategic implementation and operational excellence of automation and artificial intelligence initiatives for ASPIRE Managed Services.

This role leads the identification, design, and deployment of intelligent automation solutions to improve operational efficiency and productivity, enhance decision making, scale operations and deliver a competitive advantage in the market.

Key Responsibilities:

• Develop and execute the ASPIRE Managed Services automation and AI strategy aligned with SRG and EA Practice goals
• Identify opportunities for AI and automation across all Managed Service functions, tooling and processes
• Champion a culture of innovation and continuous improvement through emerging technologies
• Lead end-to-end delivery of automation and AI projects, including planning, development, testing, deployment, and monitoring
• Establish governance frameworks and best practices for AI and automation initiatives
• Oversee the design and implementation of AI models, RPA (Robotic Process Automation), and intelligent workflows
• Ensure solutions are scalable, secure, and compliant with data privacy and ethical standards
• Evaluate and select appropriate tools, platforms, and vendors
• Collaborate with business units to understand pain points and co-create solutions
• Communicate complex technical concepts to non-technical stakeholders
• Monitor performance and continuously optimise solutions.
• Delivery of measurable business value through automation and AI
• Development of internal capabilities and knowledge sharing across teams

Qualifications

Skills, Education & Qualifications:

• Proven experience (5 years +) leading automation and AI projects in a complex, multi-client or enterprise-scale managed services environment, with demonstrable delivery of measurable business outcomes
• Proven experience delivering Microsoft AI-powered automation solutions for enterprise-scale infrastructure estates, including Windows, Linux, and multi-vendor databases.
• Expertise with Microsoft Azure AI and automation services, such as:
• Azure OpenAI for natural language-driven insights and recommendations
• Azure Machine Learning for predictive analytics and model deployment
• Azure Monitor, Log Analytics, and Sentinel for intelligent event correlation and alerting
• Azure Automation / Logic Apps / Power Automate for workflow orchestration and remediation
• Integration experience with enterprise platforms (e.g., ServiceNow, Salesforce) to enable automated incident creation, change management, and proactive service operations.
• Performance tuning and predictive infrastructure monitoring using ML models to forecast service degradation and automate remediation actions before user impact.
• Automation of patch management, configuration drift detection, and compliance enforcement across diverse systems and database platforms.
• Advanced use of AI/ML to correlate infrastructure events with engineer resource allocation for faster Mean Time to Resolution (MTTR) and improved preventative maintenance.
• Strong understanding of operational data pipelines, ensuring telemetry from multiple systems is normalised, enriched, and leveraged for actionable insights.
• Experience in AI-driven preventative maintenance strategies, reducing unplanned outages and optimising infrastructure performance at scale.