Principal Engineer, Gen AI
*Sydney or Melbourne locations*
Shape how AI models are evaluated, served and adopted across one of Australia’s largest technology environments
Build a new enterprise capability spanning platform engineering, AI performance and engineering productivity
Influence technical strategy while remaining close to architecture, software and measurable delivery outcomes
Do work that matters
Generative AI is changing how software is designed, built, tested and operated. We are establishing a new organisation-wide engineering capability to help CommBank apply these technologies effectively, safely and at scale.
As a Principal Engineer, you will define the patterns, platforms and measurement frameworks needed to understand how AI models perform engineering work. You will help teams select, evaluate, serve and route models based on quality, cost, risk and the needs of the engineering task.
This is not primarily a model-development or research role. It is an opportunity to build the infrastructure and engineering practices that turn rapidly evolving AI capabilities into reliable, measurable and reusable solutions.
See yourself in our team
You will join a new team within the Chief AI Office, with the broader function focused on using data and AI to create world-class experiences, build capability and enable better ways of working across CommBank
In this role, you will:
Set technical direction for platforms supporting AI-model benchmarking, evaluation, serving and intelligent routing.
Design and build scalable infrastructure that allows engineering teams to use specialised and general-purpose models effectively.
Create measurement frameworks for model quality, engineering performance, reliability, adoption and cost.
Establish practical patterns and guardrails for responsible AI use across software delivery, CI/CD, risk and operational processes.
Partner with platform, engineering, product and risk teams to identify opportunities and translate them into reusable capabilities.
Evaluate emerging tools and approaches, making clear trade-offs across performance, resilience, security, cost and speed.
Write software, contribute to system design and remain hands-on with complex technical problems.
Mentor engineers, influence senior stakeholders and build organisational capability through open learning and knowledge sharing.
CommBank’s engineering AI capability already includes AI-assisted code review and testing, engineering metrics, internal knowledge tools and agentic engineering products. The next phase is focused on scaling these capabilities and applying stronger measures of value, efficiency and resilience.
We’re interested in hearing from people who:
Bring deep platform, infrastructure or software-engineering capability, together with practical exposure to machine learning or AI systems. You will be comfortable operating where outcomes are probabilistic, requirements evolve quickly and strong engineering judgement matters more than certainty.
Experience in several of the following will help you succeed:
Working seamlessly across data science and engineering disciplines and tool sets
Leading complex engineering initiatives and setting technical strategy across multiple teams.
Designing resilient cloud or platform services, including APIs, observability, automation and CI/CD.
Practical application of AI or machine-learning to technical problems, particularly model selection, evaluation, benchmarking or routing.
Developing production software using languages such as Python, TypeScript, Java, Go or C#.
Working with uncertain measures and designing experiments that produce meaningful, defensible evidence.
Secure engineering, reliability practices and responsible AI controls.
Influencing technical and non-technical stakeholders while explaining complex trade-offs clearly.
Coaching engineers and lifting standards, practices and capability across an organisation.
A background in mathematics, statistics, physics or engineering…