About Us

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.

About the Role

As an ML Ops Engineer in the Complaint Uplift Program, you will be accountable for managing and supporting the data and AI/agent pipelines required to support the usage of Generative AI models to measure and assure the Complaints quality processes. You will help establish and validate the monitoring, change and support requirements, and support build of the processes, methods and pipelines for Data Engineers and AI Engineers to use for the end to end process. You will lead the embedding of these frameworks for stakeholders to use to understand overall performance and management of the solution.

You will undertake these activities in a cross functional squad supported by external consultants and comprising Complaints SMEs, Business Analysts, AI Engineers and more. You will be collaborating to support the achievement of project or business outcomes such as process mapping and change transition as well as the technical implementation of the data and AI processes. Working alongside Teams in Customer Resolutions, Data Portfolio, ANZ*Plus, Assurance as well as key support partners in Risk, Technology and Operations, the Data Engineer plays an integral role in ensuring Project success.

You will ensure delivery of best practice end-to-end ML Ops engineering respecting ANZ policies and standards. Aligned with the broader move to a Data Mesh and Data Product architecture on cloud platforms, you will help establish the starting point for other Data Portfolio teams to move to our next state architecture.

Role Type: 12 Month Fixed Term
Role Location: Melbourne
Work Hours: Full Time

What will your day look like?

• Design and implement scalable AI solutions that enables data engineers and AI Engineers to train, build and maintain machine learning models (especially models and agents using Large Language Models/GenAI) effectively.
• Develop automated processes for continuous model/agent training and evaluation pipelines specifically for AI applications.
• Ensure the seamless integration of current architecture and processes with newly added AI and agent functionalities, enhancing overall system and process capabilities.
• Collaborate in design of data structures and processes for data ingestion, integration and analytics layers on a variety of Google Cloud Platform (GCP) technologies (e.g. Cloud Run, CloudSQL, Google Cloud Storage, BigQuery, Vertex AI) and tooling such as DBT working together to support the Complaints Quality processes.
• Working in a cross skilled squad with people both from business and technology to build end to end capabilities and support project deliverable outcomes.

What will you bring?

• A strong background in data processing and software engineering and can build high quality, scalable data and ML/AI pipelines
• Strong Software Engineering experience with proficiency in at least one high-level programming language (Python, Java, Scala, Go)
• Experience and proficiency in Google Cloud Platform technologies
• Experience with containerization, Terraform, and GitOps principles for automation and deployment.
• Strong understanding on the management of Generative AI techniques in the way we work and the outputs we generate, including emerging viewpoints on managing on agentic architecture.
• Documentation - Anticipating documentation needs for both technical and non-technical audiences, coaching others, and contributes to organizational documentation standards, including in support of knowledge management and data management needs.
• Incident, Risk and Issue Management - Independently assesses operational risks, applies security policies to mitigate issues, leads strategic incident management, and mentors others for effective response.
• Change Management - Developing and implementing change plans, analysing culture and readiness, with minimal guidance.
• Agile practices, Data & AI Privacy & Ethics - Effectively participates in Agile teams, adapting to iterative processes and new ways of working. Applying data and AI risk, privacy laws and ethical guidelines to ensure compliance in various data-related activities.
• Testing, Tools & system - Responsible for developing advanced testing methodologies, creating comprehensive strategies, mentoring teams to ensure high-quality deliverables, and applying domain knowledge to independently solve problems and improve systems or processes.

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 https://www.anz.com.au/careers. You can apply for this role by visiting ANZ Careers and searching for reference number 96248 .
 

Job Posting End Date

11/06/2025 , 11.59pm, (Melbourne Australia)