GM Data & AI Platform

About Us Standard At ANZ, we're shaping a world where people and communities thrive, driven by a common goal: to improve the financial wellbeing and sustainability of our millions of customers. Within Group Technology we're applying new ways technology and data can be harnessed as we work towards a common goal: to improve the financial wellbeing and sustainability of our millions of customers. Our community of over 5,000 engineers is key to making this happen, because technology underpins every part of our business - from delivering tools, apps and services for our customers, to building a bank for the future. About the Role The GM – Data and AI Platforms is responsible for the strategy, build, and operation of the organisation’s enterprise data and AI platforms. This role ensures the provision of secure, scalable, and high-performing platforms that enable data-driven decision-making, advanced analytics, and AI innovation across the business. Reporting to the Chief Data & AI Officer, this role owns the end-to-end platform ecosystem, including data platforms, AI/ML platforms, and associated tooling and practices. This role will ensure that platforms meet regulatory and security requirements while delivering seamless, reliable access to high-quality data and AI services for business and technology teams. As a senior leader, this role will balance platform stability, cost, innovation, and scalability ensuring that enterprise platforms underpin the organisation’s data and AI ambitions. Role Type: Permanent Role Location: Melbourne or Brisbane or Sydney Work Hours: Full Time What will your day look like? Define and own the enterprise Data and AI platform strategy and roadmap Align platform evolution with data strategy, AI strategy, and business priorities Identify opportunities for modernisation, consolidation, and capability uplift Accountable for the delivery, operation, and continuous improvement of shared data and AI platforms Ensure platforms are highly available, scalable, and performant Oversee lifecycle management across platform design, build, run, and optimisation Provision and operate AI and Generative AI platforms to support experimentation and production workloads Enable efficient model development, deployment, and lifecycle management (MLOps) Enable delivery of curated, governed data products that support analytics, reporting, and AI use cases Ensure platforms meet regulated banking and enterprise requirements (security, privacy, resilience, compliance) Own platform financials, including budgeting, forecasting, and cost optimisation Define and enforce platform engineering standards, tooling, and best practices Drive adoption of modern engineering approaches (cloud-native, automation, infrastructure-as-code) Partner with AI Portfolio, Data, Architecture, and business teams to align platform capabilities with demand Enable teams through clear SLAs, service models, and support structures Build and lead a high-performing platform engineering and operations team Develop organisational capability in data engineering, platform engineering, and AI infrastructure What will you bring? Deep expertise in data platforms, AI/ML platforms, and cloud-based architectures Proven experience defining and delivering enterprise platform strategies and roadmaps Strong knowledge of modern data ecosystems (data lakes, warehouses, streaming, data products) Experience with AI/ML and Generative AI platforms and MLOps practices Strong understanding of security, privacy, and regulatory requirements in a regulated environment (e.g., banking) Demonstrated capability in operating large-scale, highly available platforms Experience managing platform costs, budgets, and vendor relationships Strong leadership in platform engineering, DevOps, and cloud-native practices Excellent stakeholder engagement and ability to align platform capabilities with business needs Platform product mindset, treating data and AI platforms as products with clear users, value propositions, and SLAs Balancing innovation with stability, enabling rapid AI experimentation while maintaining enterprise-grade reliability Strategic cost optimisation, managing high-cost compute (e.g. AI workloads) efficiently at scale Master’s degree or PhD degree in Computer Science, Engineering, Actuarial Studies , Data Science or AI with 15y+ proven, hands on enterprise deployment experience in financial services . So why join us? From the moment you join ANZ, you'll be doing meaningful work that will shape a world where people and communities thrive. But it's not just our customers who'll feel your impact. You'll feel it too. Because at ANZ, you'll have the resources, opportunities, and support you need to take the next big step in your career. We're a diverse bunch at ANZ in different roles, different locations, doing different things. That's why we have a range of flexible working arrangements, so our people can 'make work, work for them'. We also provide a range of benefits including access to health and wellbeing services and discounts on selected products and services from ANZ and more. At ANZ, you'll be part of an organisation where the different backgrounds, perspectives and life experiences of our people are celebrated. That's because we're committed to building a workplace that reflects the diversity of the communities we serve. We welcome applications from everyone and encourage you to talk to us about any adjustments you may require to our recruitment process or the role itself. If you're a candidate with a disability or access requirement, and have an enquiry about the support provided, please let us know on your application or visit ANZ Accessibility and Inclusion Programs for alternate contact methods. To find out more about working at ANZ, visit . You can apply for this role by visiting ANZ Careers and searching for reference number 126116 . Job Posting End Date 5 November, 11.59pm, (Melbourne Australia)