Principal AI Engineer
Confirmed on the employer's own hiring board on Nov 14, 2026. First seen by Alion on Sep 29, 2026. Westpac scores A on the Alion truth index.
- Sydney, Melbourne or Brisbane Based / Hybrid Working
- Help define Westpac’s next chapter of AI Engineering.
Opportunity is knocking …
The Chief AI Innovation Office within Data, Digital & AI (DDAI) is seeking a hands-on technical authority to shape Westpac’s most important AI engineering initiatives.
You will work across teams and domains, setting directions, solving complex delivery challenges, and creating reusable approaches that help our engineers move safely from ideas to production.
It’s an exciting time for Westpac as you help shape enterprise AI engineering at a pivotal point in its evolution, with scope across production systems, reusable platforms, agentic engineering, responsible AI, and developer experience.
You’ll be a key contributor who will lift capability across teams and turn strategic AI priorities into secure, scalable production systems.
Core Role Focus …
- Architect and engineer production-grade LLM, RAG, plus agentic and machine-learning systems.
- Stay hands-on: write and review code, test assumptions, lead investigations and unblock critical delivery.
- Create reusable platforms, reference architectures, guardrails, and golden paths that accelerate multiple teams.
- Balance model quality, latency, resilience, cost, security, privacy, risk, and customer impact.
- Embed evaluation, observability, testing, responsible AI, and operational readiness from day one.
- Coach engineers through code reviews, design reviews, pairing, and practical technical leadership.
- Influence engineering, product, architecture, data, security, and risk partners without relying on formal authority.
What you will bring to the table …
- Deep, hands-on AI engineering experience in a large, complex, or regulated environment.
- Principal, Staff, Lead or equivalent experience influencing across teams and technical domains.
- Proven delivery and operation of AI, ML or LLM-enabled systems at production scale, not only proofs of concept.
- Strong Python, APIs, distributed systems, cloud, containers, infrastructure as code, CI/CD, and secure engineering capability.
- Practical expertise in LLMs, RAG, embeddings, agents, orchestration, evaluation, context management, and AI observability.
- Exceptional business acumen and outstanding stakeholder management skills at all levels.
- Sound judgement across AI failure modes, responsible AI, security, privacy, reliability, and operational risk.
- A track record of simplifying ambiguity, setting adopted standards and growing engineering capability.
Your impact:
- AI initiatives move beyond prototypes into trusted enterprise services.
- Teams deliver faster through reusable patterns.
- Risks are designed out early.
- Engineers grow stronger because you leave behind better judgement, platforms, and practices.
Does this sound like you?
To get started, simply click on the APPLY or APPLY NOW button. Please note that application closing dates are subject to change so don’t delay putting your best foot forward!
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