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Lead the design, development, and productionisation of agentic AI workflows, LLM-powered applications, and multi-agent systems
Productionise classical ML models (e.g. classification, regression, time-series forecasting), ensuring they meet production-grade standards for reliability, monitoring, and retraining
Own and evolve end-to-end MLOps and LLMOps pipelines including CI/CD, model registry, drift detection, retraining, and automated evaluation
Build and maintain scalable ML infrastructure on Azure and Databricks including feature engineering pipelines and data platform integrations
Architect and build AI agent workflows, endpoints, gateways, and orchestration layers enabling secure tool usage, structured reasoning, and multi-agent collaboration
Deploy and optimise AI workloads on Kubernetes and cloud-native Azure environments
Define and enforce engineering quality standards through code reviews, design reviews, and technical documentation
Requirements:
Tertiary qualifications in Computer Science, Software Engineering, Data Science or a related field or equivalent practical experience
Proven experience deploying and operating production-grade agentic AI systems, LLM-powered applications, or ML pipelines with commercial impact
Strong Python programming skills and deep knowledge of modern AI/ML frameworks (e.g. LangGraph, LlamaIndex, PyTorch, scikitlearn)
Solid understanding of classical machine learning, including supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), and time-series forecasting, with hands-on experience taking models to production
Strong experience with Azure cloud services (Azure ML, Azure DevOps, Azure Container Services, Azure Function Apps) and Databricks
Nice to have:
Relevant Azure certifications (e.g. Azure AI Engineer Associate, Azure Solutions Architect, Azure Data Scientist Associate)
Experience with front-end technologies (e.g. TypeScript, React) or infrastructure tooling (e.g. Terraform, Bicep) for building AI powered interfaces or managing cloud-native deployments
Experience building data engineering pipelines
Demonstrated contributions to open-source AI projects or published technical work
What we offer:
Individualised Learning & Development pathway options
Access to 'LinkedIn Learning' for ongoing skills development: over 24,500 courses in over 20 languages
Exclusive Staff Discounts: Accessible via our employee-only portal with 350+ of Australia’s leading retailers, health and wellness discounts, financial planning advice, employee share plan and more
Travel Discounts: Including family and friends - flights, hotels, tours, cruises, travel insurance and more
Brightness of Future: Career opportunities in a network of brands and businesses across the globe - we promote from within
Corporate Health Discounts: Access exclusive discounts on health insurance plans for you and your family with our partner, BUPA, access to internal gym
Mental Health: Support and Employee Assistance Program for staff and family
Social: Regular awards nights, social team-building and industry events, with the opportunity to attend global conferences (Bangkok in 2026)
Giving Back: Corporate Social Responsibility program supporting nominated charities through Workplace Giving, volunteering and fundraising
paid parental and volunteer leave
Sustainability
Be part of a workplace committed to reconciliation through our Reconciliation Action Plan