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
• Strong technical expertise in Artificial Intelligence and Machine Learning, including:
• Supervised/unsupervised learning, deep learning, and natural language processing (NLP)
• Model development using frameworks such as TensorFlow, PyTorch, or scikit-learn
• Experience deploying AI models in production environments using MLOps principles (e.g., MLflow, Azure ML, SageMaker).
• Hands-on experience with automation and orchestration technologies, such as:
• Robotic Process Automation (RPA) platforms: UiPath, Blue Prism, Automation Anywhere
• IT process automation (ITPA) tools: ServiceNow Workflow/Orchestration, Microsoft Power Automate, Ansible, Terraform
• Integration using APIs and event-driven architectures (e.g., Kafka, Azure Event Grid)
• Proficiency in cloud-native AI and automation services in one of or more of public cloud platforms:
• Azure (Cognitive Services, Synapse, Logic Apps, Azure OpenAI)
• AWS (SageMaker, Lambda, Textract, Step Functions)
• GCP (Vertex AI, AutoML, Cloud Functions)
• Strong project delivery experience using modern methodologies:
• Agile/Scrum and DevOps for iterative development and deployment
• CI/CD pipeline integration for automation and ML model lifecycle management
• Use of tools like Git, Jenkins, and Azure DevOps
• In-depth knowledge of data architecture, governance, and AI ethics, including:
• Data privacy and security principles (e.g., GDPR, ISO 27001)
• Responsible AI practices: bias detection, explainability (e.g., SHAP, LIME), model drift monitoring
• Excellent stakeholder engagement and communication skills, with the ability to:
• Translate complex AI and automation concepts into business value
• Influence cross-functional teams and executive leadership
• Promote a culture of innovation, experimentation, and continuous learning
• Excellent leadership and team management skills
• Strong communication, interpersonal, and problem-solving abilities
• Strategic thinking and decision-making
• Adaptability to evolving technologies and processes
• Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent experience