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About the Role
As a Staff Platform Engineer, you’ll shape and evolve the platform capabilities that enable teams to build, deploy and operate AI/ML workloads safely and efficiently. Combining deep technical expertise with hands-on engineering leadership, you’ll turn complex platform challenges into reusable solutions. Your focus will span AI/ML Operations (MLOps), self-service automation, production reliability and resource efficiency, helping teams deliver faster without compromising security or operational control. You’ll influence technical direction across teams, establish practical engineering standards and tackle the systemic issues that create operational toil, instability or unnecessary cost. This is a hands-on technical leadership role, with impact measured through stronger platform capabilities, improved developer experience and sustainable operational outcomes.
Responsibilities
- Build and evolve AI/ML platform capabilities that support repeatable training, evaluation, deployment, serving and monitoring of models across their production lifecycle.
- Make secure delivery repeatable, embedding versioning, traceability, automated checks, controlled promotion and rollback into AI/ML deployment workflows.
- Drive automation and self-service, developing reusable infrastructure, deployment patterns and operational tooling that reduce manual effort and simplify platform adoption.
- Lead operational improvement, using incidents, performance trends and recurring support issues to address root causes and prevent repeat failures.
- Champion FinOps, making platform consumption and cost visible, strengthening ownership and helping teams understand the cost implications of engineering decisions.
- Optimise platform efficiency, improving workload scheduling, scaling, resource utilisation and capacity management while balancing cost, performance and resilience.
- Embed security and operational controls into platform design, working with security, architecture and risk partners to make compliant engineering practices easier to adopt.
- Provide Staff-level technical leadership, shaping platform roadmaps, leading complex design decisions and aligning teams around reusable solutions rather than fragmented implementations.
Requirements
- Strong software engineering skills, including Python or another relevant programming language, API development, automated testing and maintainable tooling.
- Deep understanding of cloud-native engineering, containers, Kubernetes, infrastructure as code and automated delivery practices.
- Practical experience taking AI/ML workloads into production, including model pipelines, artefact and version management, deployment, serving and monitoring.
- Understanding of the operational needs of AI/ML workloads, including reproducibility, data and model dependencies, compute requirements and production performance.
- Ability to translate complex requirements into secure, reusable platform capabilities that engineers can adopt with minimal friction.
- Strong experience applying reliability engineering practices, including service-level objectives, observability, capacity planning, incident response and recovery.
- An automation-first mindset, with demonstrated experience eliminating recurring manual work and improving developer and operator experience.
- Experience applying FinOps principles, including cost allocation, consumption visibility, rightsizing and workload optimisation.
- Ability to assess cost, performance and resilience trade-offs, including the resource demands of AI/ML training and inference.
- Experience embedding security, access controls and operational governance into engineering workflows.
- Strong technical judgement and the ability to influence across teams, mentor engineers and turn engineering improvements into measurable outcomes.
Skills
- Python
- API development
- Automated testing
- Maintainable tooling
- Cloud-native engineering
- Containers
- Kubernetes
- Infrastructure as code
- Automated delivery
- AI/MLOps
- Model pipelines
- Artifact management
- Version management
- Deployment
- Serving
- Monitoring
- Reproducibility
- Data dependencies
- Model dependencies
- Compute requirements
- Production performance
- Reliability engineering
- Service-level objectives
- Observability
- Capacity planning
- Incident response
- Recovery
- FinOps
- Cost allocation
- Consumption visibility
- Rightsizing
- Workload optimisation
- Security
- Access controls
- Operational governance
Location
- Remote
Work Type
- Full-time
Experience Level
- Staff-level
About the Company
- At CommBank, we’re committed to creating an accessible, inclusive and respectful workplace.
- We treat platforms as products, with clear ownership, reusable capabilities and a strong understanding of the teams who depend on them.
- We're keen to support you with the next step in your career.
Equal Opportunity
- We welcome applications from people of all backgrounds and we’re particularly committed to making a positive difference for Aboriginal and/or Torres Strait Islander Peoples.
- If you require support or adjustments, please let us know.
- We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696.