About the Role

In this role, you will:

• Design, build, test and deploy enterprise grade AI solutions and agentic workflows across MS Azure and Databricks ecosystems.
• Using manual and spec-driven techniques, develop clean, testable and well-documented Python, C# and SQL code that meets engineering standards and supports long-term supportability.
• Develop integrated PDLC and DDLC agent workflows which delivery software applications, data pipelines and products.
• Build AI solutions using frontier and open weight models using RAG, VectorDBs, Knowledge Graphs and MCP servers.
• Use Azure AI Foundry, Databricks Mosaic AI and approved AI engineering tools to support solution development and delivery.
• Contribute across the delivery lifecycle, including problem framing, data exploration, prototyping, feature engineering, model evaluation, deployment, monitoring and support.
• Design and maintain MLOps pipelines, including CI/CD for machine learning, automated model training, evaluation gates, deployment and monitoring.
• Manage experiment tracking, model versioning and reproducibility through the Databricks MLflow model registry.
• Implement solution performance monitoring with evaluation agents for drift detection, hallucination, and model performance degradation.
• Apply spec-driven development, DevOps, secure-by-design, responsible AI and human-in-the-loop review practices.
• Contribute to engineering standards, code reviews, prompt reviews, technical design sessions and agile delivery ceremonies.
• Produce and maintain technical documentation, including architecture decision records, runbooks, model cards, data lineage records and pipeline documentation.
• Support and mentor junior engineers through knowledge sharing, pairing and agent-assisted delivery walkthroughs.
• Work with architecture, governance and cyber security teams to ensure solutions meet Downer’s enterprise, security and responsible AI standards.
• Contribute to cost optimisation and FinOps practices across Azure Databricks and Azure AI Foundry.

This is an opportunity to contribute to Downer’s uplift in AI-native delivery while developing your technical depth across modern AI/ML engineering, agentic workflows and governed enterprise AI.

About the Role

In this role, you will:

• Design, build, test and deploy enterprise grade AI solutions and agentic workflows across MS Azure and Databricks ecosystems.
• Using manual and spec-driven techniques, develop clean, testable and well-documented Python, C# and SQL code that meets engineering standards and supports long-term supportability.
• Develop integrated PDLC and DDLC agent workflows which delivery software applications, data pipelines and products.
• Build AI solutions using frontier and open weight models using RAG, VectorDBs, Knowledge Graphs and MCP servers.
• Use Azure AI Foundry, Databricks Mosaic AI and approved AI engineering tools to support solution development and delivery.
• Contribute across the delivery lifecycle, including problem framing, data exploration, prototyping, feature engineering, model evaluation, deployment, monitoring and support.
• Design and maintain MLOps pipelines, including CI/CD for machine learning, automated model training, evaluation gates, deployment and monitoring.
• Manage experiment tracking, model versioning and reproducibility through the Databricks MLflow model registry.
• Implement solution performance monitoring with evaluation agents for drift detection, hallucination, and model performance degradation.
• Apply spec-driven development, DevOps, secure-by-design, responsible AI and human-in-the-loop review practices.
• Contribute to engineering standards, code reviews, prompt reviews, technical design sessions and agile delivery ceremonies.
• Produce and maintain technical documentation, including architecture decision records, runbooks, model cards, data lineage records and pipeline documentation.
• Support and mentor junior engineers through knowledge sharing, pairing and agent-assisted delivery walkthroughs.
• Work with architecture, governance and cyber security teams to ensure solutions meet Downer’s enterprise, security and responsible AI standards.
• Contribute to cost optimisation and FinOps practices across Azure Databricks and Azure AI Foundry.

This is an opportunity to contribute to Downer’s uplift in AI-native delivery while developing your technical depth across modern AI/ML engineering, agentic workflows and governed enterprise AI.