Staff Platform Engineer - AI/ML

Staff Platform Engineer - AI/ ML

• We are a growing team within the bank and constantly involved in industry changing solutions

• You will be part of an innovative environment with likeminded individuals

• Together we can place customers at the centre of what we do 

Do work that matters:

The Fraud & Scams Analytics team, part of the Chief Data and Analytics Office, maintains the fraud detection and reporting functions for the Group. Our team supports the operations of Group Security who are devoted to protecting the monetary assets from fraud and financial loss of CBA and Bankwest customers.

As part of the Platform Engineering team, you’ll contribute to strategic initiatives like improving the standards of Fraud & Scam Analytics, AI-powered engineering, and reliability uplift. You’ll work alongside top collaborators to solve our customers’ most complex data-centric problems.

See Yourself in our team:

This role blends Platform Engineering and Software Engineering with a strong AI mindset and AI Ops capabilities. You’ll design, build, and evolve application, tooling, and automation that empower product teams to deliver customer value with speed, safety, and reliability. You’ll also champion AI-powered engineering practices and embed intelligent automation into operations, observability, and service management.

Our team’s diverse backgrounds means we can draw on one another’s experience to deliver to best work outcomes. We are committed to safe-guarding our customers from financial fraud and scams. Our analytics run on Australia’s largest real-time transaction monitoring system, handling millions of transactions per day.

We’re interested in hearing from people who can:

Platform Engineering

• Build secure, scalable, and self-service platforms using Infrastructure-as-Code and cloud-native services (AWS preferred)

• Develop standardised tooling for deployment, monitoring, and operations. Automate infrastructure provisioning and operations using Python, Go, and Terraform

• Continuously evolve platform capabilities to embrace new technologies and improve developer experience

ML Engineering

• Experienced in design and implementation of scalable, end-to-end ML systems including data pipelines, model training infrastructure, and production serving platforms

• Establish robust MLOps practices including automated model deployment pipelines, comprehensive monitoring and observability, A/B testing frameworks, and model performance tracking

• Collaborate with data scientists, product teams, and infrastructure engineers to translate ML research into production systems.

AI & AIOps Enablement

• Embed AI-powered engineering tools (e.g., GitHub Copilot, autonomous agents, anomaly detection) into platform and reliability workflows

• Leverage Gen AI and agentic frameworks to automate diagnostics, remediation, and service management

• Drive adoption of AI tools across squads, aiming for 100% usage in FY26

• Collaborate on initiatives like Gen AI chatbot and self-service analytics platforms

Strategic Impact

• Influence architecture and design decisions with a focus on operability, automation, and AI integration

• Partner with squads to uplift DevSecOps maturity and reduce toil through intelligent automation, observability and CICD

• Contribute to Frauds AI strategy and maturity curve, including ethical AI and multi-agent frameworks

People Leadership & Chapter Responsibilities

• Lead and mentor a chapter of engineers, fostering a culture of technical excellence, collaboration, and continuous learning

• Provide coaching and career development support to chapter members, aligning individual growth with strategic goals

• Facilitate cross-functional collaboration across squads, ensuring alignment on platform initiatives and engineering standards. • Represent the chapter in leadership forums, contributing to strategic planning and capability uplift

• Promote psychological safety and inclusive practices within the chapter and broader engineering community

Tech Skills & Experience

• Strong coding skills in Python, Go, or similar languages

• Deep experience with AWS, CI/CD, ML and Infrastructure-as-Code

• Proven track record in platform engineering, cloud infrastructure, and reliability practices

• Familiarity with AI tools, frameworks, and AIOps platforms (e.g., anomaly detection, self-healing pipelines)

• Experience with observability tools (e.g., Prometheus, Grafana) and incident management

• Experience with Snowflake is desirable

• Excellent collaboration and communication skills across technical and business domains

If you thrive on creating lasting, impactful technology and want to be part of an inclusive team that values innovation and growth, we’d love to hear from you!

We support our people with the flexibility to balance where work is done with at least half their time each month connecting in office.

Working with us: 

Our people bring their diverse backgrounds and unique perspectives to build a respectful, inclusive, and flexible workplace with an ultimate flexibility to work from any of our engineering hubs within Australia. One where we’re driven by our values, and supported to share ideas, initiatives, and energy. One where making a positive impact for customers, communities and each other is part of our every day.