Description Sydney or Melbourne Location / Hybrid Working Are you ready to make your mark? As an AI Engineer in the General Business Units (GBU) Data Platforms (DP) team, you’ll build, deploy, and operationalise enterprise AI and Generative AI on Westpac’s strategic data platforms. Working in cross-functional squads, you’ll engineer production-ready ML, agentic and GenAI solutions—pipelines, APIs, and model deployments—that are secure, dependable, and scalable. You’ll partner with data scientists, engineers, and product teams to embed AI into core data products and workflows, improving customer outcomes and operational efficiency. Complementing a well-established Data Platforms engineering team that is now expanding into Enterprise AI capabilities, you’ll also help build the foundations, influence the direction, and play a key role in delivering scalable AI solutions that will support critical business functions across the bank. Westpac has been serving customers for over 200 years, and you’ll play a key role in shaping its future through modern engineering and AI innovation. Key areas of responsibility … Design, build and deploy ML and AI applications for business and operational problems. Engineer scalable pipelines and APIs for batch, streaming, and real-time workloads. Build and operationalise GenAI solutions (prompt engineering, RAG, agents, fine-tuning). Integrate, deploy, monitor, and optimise models in production for performance and resilience. Apply MLOps and engineering best practices (CI/CD, testing, versioning, monitoring). Analyse large structured/unstructured datasets; troubleshoot pipeline/model issues. Maintain documentation and evaluate emerging AI/GenAI technologies. Key ingredients for success … Degree qualified in a relevant technical discipline. Passion, drive, natural curiosity, underpinned by a continuous improvement mindset. Solid working experience in corporate or professional services building and deploying ML models in production. Strong Python/software engineering skills. Hands-on GenAI delivery experience (prompting, RAG, agents, LLM integration); frameworks such as LangChain/LlamaIndex/AutoGen/DSPy. Cloud experience (Azure/AWS/GCP); Docker/Kubernetes. Experience with large-scale data platforms (e.g., Spark, ADLS) and CI/CD (Git, testing). Highly desirable ingredients … Enterprise AI/platform experience; MLOps lifecycle management. Streaming/real-time systems; experimentation and model evaluation. Strong problem-solving in complex environments. Why join us? We are committed to supporting your growth through: Access to innovative technology and large-scale enterprise data platforms Strong career development pathways across engineering, AI, and platform leadership Flexible working arrangements and supportive team culture Ongoing learning, certification, and skill development opportunities Comprehensive parental leave and family support benefits A collaborative, innovative environment focused on continuous improvement. to work in complex enterprise environments. 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.