See yourself in our team:

At CBA we have an ambitious goal of leading the way in changing the world through AI. With great buy-in from all senior leadership, we have embarked on world first initiatives to deliver exceptional experiences to our customers. In Retail Banking Services (RBS), as the largest and customer facing part of the bank, we play a unique role in bringing this vision to life and build a brighter future for all Australians.

The opportunity:

Reporting to the Chapter Lead, AI, you will deliver high priority initiatives across RBS. You will work on the delivery of world-class AI capabilities across RBS that will also build capabilities for the rest of CBA. You will work with cutting edge initiatives in Agentic AI, GenAI, and broader AI. Our strategic focus lies in delighting our customers at every touchpoint, offering outstanding service, and meet the needs of our customers.

Why CommBank?

CommBank is leading the world of banking by venturing into new-to-the-world innovations. We're on the cutting edge, embracing AI technologies to reshape how we operate and serve our customers.

Key Responsibilities:

· GenAI and Agentic system design and development: Drive the expansion and adoption of Generative AI solutions across RBS, optimising our product offerings through design and implementation of advanced Gen AI capabilities and agentic AI systems.

· Develop and implement Machine Learning Models: Lead the overhaul of various machine learning models, enabling to drive strategic business outcome for various stakeholders.

We’re interested in hearing from people with the following skills.

· Proven commercial experience in Gen AI, chatbot development, and LLMs.

· Strong foundation in statistics and probability; able to interpret models.

· Proficiency in Python and experience with AI/ML model development.

· Excellent communication skills for documentation and stakeholder engagement.

· Tertiary qualification in Data Science, Statistics, Computer Science, or a related field.

Technical Skills and Tools:

We use a broad range of tools, languages, and frameworks. We don’t expect you to know them all but experience or exposure with some of these (or equivalents) will set you up for success in this team.

· Machine Learning: Expertise in the design and construction of machine learning models, including feature engineering, model selection, hyperparameter tuning, model evaluation, and deployment of predictive models into production environments.

· Generative AI: Familiarity with various aspects of Generative AI, including prompt engineering, Retrieval-Augmented Generation (RAG), guardrail design, orchestration design, and tools such as LangChain and LangGraph.

· Cutting-Edge AI: Work on projects leveraging traditional AI, Generative AI, and agentic AI to pave the path for how banking and broader industry functions in the future.

· Version Control and CI/CD: Experience with version control and CI/CD pipelines such as GitHub.

· Tooling: Hands-on experience with data science tools such as Spark, Python, R, TensorFlow, PyTorch, and SQL.

· Data Engineering: Knowledge of ETL processes and data pipeline construction, ensuring efficient data flow and integration.

· Deployment: Familiar with Docker for containerization and deployment of applications.

· Cloud Architecture: Grounded understanding in AWS or Azure Cloud architecture and integration, demonstrating experience in deploying and managing cloud-based solutions.

Our Talent Acquisition team will be taking a scheduled break over the festive period beginning 24 December. We will resume reviewing applications and responding to enquiries from 5 January. We appreciate your understanding and patience during this time and wish you a safe and enjoyable holiday season