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NTT DATA Logo NTT DATA · IT - Software Development

Director AI & Automation

Australia, Sydney · Job Posted June 28, 2026
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Job Description

This is a high impact leadership role for someone who loves challenging the status quo, can see where work should be simplified or automated, and can bring people on the journey. Build trusted, scalable and measurable agentic ways of working. Deliver measurable impact at scale. Turn ideas into adoption, adoption into operational change, and operational change into measurable business value.

Job Responsibility

  • Lead the ANZ Managed Services Delivery AI and Automation agenda, aligned to Group and APAC agentic workforce transformation programs
  • Own year-on-year efficiency outcomes across Managed Services delivery
  • Lead, coach and develop a team of AI and automation engineers/developers, ensuring they are focused on the highest value opportunities and building secure, supportable and reusable capabilities
  • Identify, assess and prioritise AI, automation and agentic use cases across delivery, operations, service management and engineering
  • Build a repeatable pathway from idea to use case, prioritisation, development, enablement, adoption and benefits realisation
  • Lead an AI and Automation Centre of Excellence that encourages innovation at the edge while scaling proven capabilities into secure, supported and reusable enterprise patterns
  • Redesign processes and workflows around human accountability, agentic execution, trust, governance and measurable outcomes
  • Partner with platform and architecture teams to ensure AI and automation solutions are secure, scalable, integrated and supportable
  • Establish governance for responsible AI and automation, including ethical design, data readiness, access control, security, ownership and operational support
  • Run workshops, hackathons, showcases and enablement programs that create energy, adoption and practical outcomes
  • Track and report value through efficiency, productivity, adoption, service quality, employee experience and operational performance metrics

Requirements

  • Leadership experience across AI, automation, service transformation, managed services, operations, digital transformation or technology delivery
  • Experience leading technical teams, including automation engineers and AI developers, platform or similar delivery capability
  • Proven experience delivering automation, AI or process transformation outcomes that improved efficiency, productivity, service quality or operational performance
  • Strong understanding of GenAI, agentic workflows, automation, workflow orchestration and enterprise AI adoption
  • Experience leading organisational change, including stakeholder alignment, communication, enablement, adoption and behaviour change
  • Ability to partner with senior leaders to turn business problems into prioritised AI and automation programs
  • Commercial discipline and experience owning efficiency, productivity, benefits realisation or operational performance targets
  • Experience building or leading a CoE, automation capability, transformation function, innovation program or enablement team
  • Understanding of responsible AI, security, privacy, data governance, ethical design and human accountability
  • Strong communication and storytelling skills, with the ability to excite, challenge and influence people at all levels
  • Genuine curiosity and passion for AI, including a willingness to experiment, prototype and stay close to the technology

Nice to have

  • Managed services, IT operations, outsourcing, systems integration or technology services
  • Microsoft AI stack such as Copilot, Azure AI, Azure OpenAI, Power Platform or Copilot Studio
  • Google AI stack such as Gemini Enterprise, Vertex AI or agentic workplace tools
  • Automation and orchestration platforms such as Ansible, Terraform, Rundeck, StackStorm, ServiceNow Flow Designer, Azure Logic Apps, GitHub Actions, GitLab CI/CD, Jenkins, or similar
  • ITSM automation, AIOps, or SRE environments
  • Human-and-agent operating models where AI agents assist, act, recommend, escalate or resolve within clear controls
  • Scaling prototypes into supported enterprise services with ownership, governance, security and support models
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