Quick overview
Job description
At Westpac, we're building responsible, human-centred AI at enterprise scale - and we're looking for hands on AI Engineers who can turn ideas into secure, scalable, production ready solutions.
You'll join our Data, Digital & AI function and work with the Westpac Chief AI Innovation Office to build practical AI capability across technology, data, risk, security, product and business teams.
This is an engineering first role for people who can design, code, integrate, test and operationalise AI applications, services, agents and platforms - beyond proofs of concept.
You'll bring strong software engineering fundamentals, practical AI/ML experience and the judgement to deliver safely in a complex, regulated enterprise environment.
Key Responsibilities -- Design, build and ship production ready AI applications, services, agents and internal tools.
- Integrate foundation models, ML models, RAG, vector stores and AI services into secure enterprise workflows.
- Build pipelines for prompt management, model invocation, grounding, validation and evaluation.
- Embed security, privacy, compliance, model risk and responsible AI guardrails from design to delivery.
- Build testing, evaluation, monitoring, and feedback loops for quality, performance, safety, and cost.
- Optimise latency, reliability, and cost across AI workloads.
- Collaborate with product, data, risk, security, and platform teams to clarify requirements, surface trade offs, and align priorities for delivery.
- Hands on AI engineering experience in large, complex corporate or regulated environments.
- Ability to deal effectively with technical and non technical stakeholders at all levels.
- Tertiary qualifications in a relevant technology, engineering, computer science, data or related discipline, or equivalent practical experience.
- Strong software engineering background across backend services, APIs and production systems.
- Practical experience operationalising LLM, ML or AI services beyond prototypes or academic projects.
- Hands on knowledge of RAG, embeddings, vector databases, orchestration and model evaluation.
- Experience with cloud, CI/CD, automated testing, observability and enterprise release practices.
- Understanding of prompt design, evaluation, safety testing and responsible AI practices.
- Ability to balance experimentation speed with engineering quality and safety.
- Comfortable working with diverse stakeholders to triage requests, communicate constraints, and prioritise work based on impact and risk.
We're all about creating a supportive and inclusive community. We welcome everyone - no matter your age, gender, background, or abilities. We also provide additional support to welcome our veterans, Indigenous Australians and neurodiverse community.
If you need any adjustments during the recruitment process, you can find out more information and additional contact details by visiting the "People with Disability and/or needing Accessibility Requirements" page on our website.
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