Senior AI Engineer - AI Innovation Office

Westpac Group; Sydney; On-site; AUD 150,000 - 210,000; Full time

Job summary

Westpac Group is seeking a senior AI Engineer to design, build and operate secure AI capabilities for enterprise-scale applications. This role emphasizes hands-on development, governance, and production readiness while collaborating with risk, security and product teams.

You will guide teams, influence engineering standards and ensure safe, reliable deployment across hybrid environments in Australia.

Qualifications

• Significant hands-on AI engineering experience gained in a complex corporate, technology or enterprise environment.
• Strong track record of delivering AI/ML/LLM-enabled systems that have been deployed, governed, monitored and operated in production.
• Solid software engineering foundations across Python, APIs, cloud services, distributed systems, CI/CD, automated testing and modern delivery practices.
• Deep practical experience with LLMs, RAG patterns, embeddings, agents, evaluation frameworks, orchestration, model lifecycle management and monitoring.
• Experience embedding safety, privacy, compliance, explainability, reliability and operational risk controls into AI solutions.
• The ability to shape technical direction, raise engineering standards and bring stakeholders with you through ambiguity and change.
• Clear communication skills across engineering, product, delivery, risk and senior stakeholder audiences.

Responsibilities

• Design, build and ship complex AI platforms, services and products that solve meaningful business problems at enterprise scale.
• Engineer robust LLM, retrieval-augmented generation, agentic and orchestration solutions, with reliability, evaluation, observability and governance built in from the start.
• Take AI capabilities from experimentation into production, including testing, deployment, monitoring, incident response and continuous improvement.
• Lift engineering standards across prompt and context management, model evaluation, security, privacy, compliance and Responsible AI guardrails.
• Make practical trade-offs across model quality, latency, cost, risk and customer impact in fast-moving delivery environments.
• Partner with product, platform, data, risk, security and business teams to scale AI safely and sustainably.
• Review designs and code, mentor engineers and establish reusable patterns that accelerate safe production delivery.
• Lead technical investigations, root-cause analysis and durable fixes for complex AI system issues.

Skills

Python

LLMs

AI Systems

Cloud services

MLOps

Strong communication

Tools

APIs

CI/CD

Docker

Job description

Australia

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Job Description

• Sydney Location / Hybrid Working
• Move beyond prototypes and help turn bold ideas into secure, scalable enterprise capability.

Are you ready to help shape how AI is engineered, governed and scaled?

Westpac is accelerating the future of banking through responsible, human-centred AI. We are looking for a senior, hands-on AI Engineer to complement the Chief AI Innovation Office within Data, Digital & AI, a team shaping how advanced analytics, digital platforms and AI are engineered, governed and scaled across a large and complex enterprise.

This is an opportunity to bring your technical depth to high-impact work, influence enterprise engineering standards and help teams move promising ideas into reliable production services.

Your role

You will design, build, test, harden and operate AI capabilities that are safe, reliable and ready for enterprise use. This is a practitioner role for someone who enjoys solving difficult engineering problems, making thoughtful trade-offs and staying close to the code and production environment.

You will lead through technical credibility and influence. You will guide others, strengthen reusable engineering patterns and help ensure AI is delivered responsibly from concept through to production.

Key responsibilities

• Design, build and ship complex AI platforms, services and products that solve meaningful business problems at enterprise scale.
• Engineer robust LLM, retrieval-augmented generation, agentic and orchestration solutions, with reliability, evaluation, observability and governance built in from the start.
• Take AI capabilities from experimentation into production, including testing, deployment, monitoring, incident response and continuous improvement.
• Lift engineering standards across prompt and context management, model evaluation, security, privacy, compliance and Responsible AI guardrails.
• Make practical trade-offs across model quality, latency, cost, risk and customer impact in fast-moving delivery environments.
• Partner with product, platform, data, risk, security and business teams to scale AI safely and sustainably.
• Review designs and code, mentor engineers and establish reusable patterns that accelerate safe production delivery.
• Lead technical investigations, root-cause analysis and durable fixes for complex AI system issues.

Key Ingredients for Success

• Significant hands-on AI engineering experience gained in a complex corporate, technology or enterprise environment.
• A strong record of delivering AI, machine learning or LLM-enabled systems that have been deployed, governed, monitored and operated in production.
• Solid software engineering foundations across Python, APIs, cloud services, distributed systems, CI/CD, automated testing and modern delivery practices.
• Deep practical experience with LLMs, RAG patterns, embeddings, agents, evaluation frameworks, orchestration, model lifecycle management and monitoring.
• Experience embedding safety, privacy, compliance, explainability, reliability and operational risk controls into AI solutions.
• The ability to shape technical direction, raise engineering standards and bring stakeholders with you through ambiguity and change.
• Clear communication skills across engineering, product, delivery, risk and senior stakeholder audiences.

What Success will look like

• AI solutions progress beyond prototypes to become trusted, secure and production-ready enterprise capabilities.
• Engineering patterns are clear, reusable and adopted across teams.
• AI risks are identified and designed out early through strong architecture, governance and operating discipline.
• Systems are observable, resilient and continuously improved using real usage, feedback and performance data.
• Engineers around you grow through practical mentoring, thoughtful design review and strong technical examples.

Does this sound like you?

We’re all about creating a supportive and inclusive community. We welcome everyone – no matter your age, gender, background, or abilities. We also provide added 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 .