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 AI Engineer in our Complaint Uplift Program, you’ll play a key role in helping to manage the analytic methods and processes required to support the usage of Generative AI models to measure and assure the Complaints quality processes. You will help establish and validate the data sourcing requirements, understand the data available and frameworks needed to be assessed and build (and support deployment of) solutions for using the available inputs to be interrogated through Generative AI/Agentic techniques to generate outputs to support quality control and assurance of the Complaints management process. You will understand the downstream consumption requirements (e.g. reporting, model monitoring and integration back to Complaints Management System/Salesforce) and ensure the analytic processes cater for those downstream requirements.

Banking is changing and we’re changing with it, giving our people great opportunities to try new things, learn and grow. Whatever your role at ANZ, you’ll be building your future, while helping to build ours.

Role Type: 9-month fixed-term contract
Role Location: Melbourne (hybrid)
Work Hours: Full-time

What will your day look like?

As an AI Engineer, 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 AI Engineer plays an integral role in ensuring Project success.

You will actively participate in feedback processes to develop and refine solutions leveraging large language models, requiring strong understanding of the purpose of the complaint quality frameworks and how to improve the use of the large language models to improve consistency, accuracy and confidence of the model outcomes. You will help establish the analytic development process to continuously refine these models and deploy new models/model versions in a controlled and measured way, including establishing best practices for change management, evolution of business and system prompts, and measuring the efficacy of these change impacts.. You will be across the different foundational models that are available and will be able to recommend and support assessment of different models in the overall framework.

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

What your typical day might look like:

• Address and solve complex business issues using large amounts of data (structured and unstructured)
• Understand the application of Generative AI in a cloud data & analytic eco-system, and develop analytical solutions that best support transformation of the Complaints quality business processes
• Continuous development, monitoring, presenting and conducting of 'fact-based' analysis and models to use at any time for the development and improvement of relevant quality management processes
• Design, build, deploy, monitor and assess relevant models for implementation as AI Agents in the complaints management value chain (identify, classify, manage, quality control, remediate)
• Design and implement best practices for Agentic AI solutions to effectively operate in an environment comprised of other heterogeneous agents with access to a diverse set of tools.
• Identify data from a variety of sources to combine, synthesise and analyse to support complaints quality management processes

What will you bring?

To grow and be successful in this role, you will ideally bring the following:

• Good understanding of the Banking system and products, service, channels in support of the understanding of the customer experience that led to the Complaint
• Highly desirable to have good knowledge of Complaints management processes, Quality Assurance processes and the relevant regulatory environment.
• Desirable to have good domain knowledge of ANZ systems
• Strong customer lens with a bias towards safety, consistency and fairness in how AI is applied to the process.
• Solid understanding of predictive modelling, pattern recognition, clustering, supervised and unsupervised learning
• Proven experience in applied probability and statistics
• Hands-on knowledge and experience with tools and techniques for analysis, data manipulation and presentation
• Experience in using open source technologies for Data Science, specifically Python and key supporting packages/libraries and development environments
• Experience in using Generative AI to solve real business challenges, ideally with multiple model families (e.g. Gemini, Anthropic, OpenAI, Meta)
• Experience with Retrieval Augmented Generation (RAG) frameworks, and best practices for generating and using embeddings.
• Use of Google Cloud Platform services such as Vertex AI and related data management services (BigQuery, CloudSQL etc).
• Ability to understand and test trade-off for model quality, performance and cost management
• Strong ability to translate model outputs and insights into practical business recommendations
• Ability to effectively communicate and present to all stakeholders (technical and non-technical)
• Data Collection and Cleaning - Leads teams in identifying data sources for large projects; extensively knowledgeable in best-practice data cleaning techniques and handling complex data issues.
• Feature Engineering - Masters a wide range of techniques and optimizes feature engineering processes.
• Machine Learning Modelling - Selects appropriate modeling techniques, translates business requirements, and systematically improves model performance.
• Model Evaluation and Validation - Ability to assess and monitor the performance of AI solutions, and assess and address drivers of poor performance.
• Data Visualisation - Draws insights from data, supports decision making, and automates data visualization.
• Soft Skills: Communication, Problem Solving, Planning & Prioritisation, Critical thinking.

You’re not expected to have 100% of these skills. At ANZ a growth mindset is at the heart of our culture, so if you have most of these things in your toolbox, we’d love to hear from you.

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 108195 .
 

Job Posting End Date

Wednesday 14th January 2026, 11.59pm, (Melbourne Australia)