AI/ML Engineer — Enterprise AI & Agentic Workflows

Downer; Melbourne; On-site; AUD 150,000 - 190,000; Full time

Benefits offered by this job

ASX-listed company

Professional development programs

Flexible work arrangements

Parental leave

Employee Assistance Program

Diversity and inclusion programs

Discounted services

Job summary

Downer is seeking six AI/ML Engineers to design, build and scale enterprise-grade AI solutions in an agentic-first environment. You will deploy production-grade models across Azure Databricks and Foundry, collaborating with architecture, security and data governance teams. Melbourne-based with travel to Downer sites as needed.

The role emphasizes hands-on development in Python, C#, and SQL, MLOps pipelines, and strong engineering discipline to deliver reliable, scalable AI products.

Qualifications

• A tertiary qualification in Computer Science, Computer Engineering, Software Engineering, Information Technology, Data Science, Mathematics, Statistics, quantitative analysis or a related discipline.
• Relevant industry certifications in Azure AI, Databricks, GitHub, software engineering, DevOps, security or cloud data platforms will be highly regarded.
• At least five years' total experience across software and/or data engineering or related technical field.
• At least two years relevant hands-on experience developing advanced analytics, machine learning or generative AI solutions for production environments.
• Practical experience with Azure and Databricks ecosystems, including exposure to Azure AI Foundry, Databricks Mosaic and Genie Code.
• Familiarity with model hosting in platforms such as Azure AI Foundry, Databricks Mosaic AI and AWS Bedrock is highly regarded.
• Experience with AI engineering tools such as Claude Code, Codex, Cursor, GitHub Copilot and Copilot Studio is highly regarded.
• Experience in DevOps engineering, CI/CD, secure-by-design principles and FinOps controls recognising the importance of balancing token-economics with performance.
• Familiarity with orchestration frameworks such as CrewAI, Strands Agents and Microsoft Agent Framework is valued, as is familiarity with spec-driven development, agentic product delivery lifecycle practices and agentic business workflows.
• Strong hands-on capability in Python, C#, SQL, Git-based version control, automated testing, code review and production-quality engineering practices.
• Practical understanding of platform controls implemented through Unity Catalog, Microsoft Purview and Agent 365 as part of an enterprise Data & AI governance ecosystem.

Responsibilities

• 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.

Skills

Python

C#

SQL

Azure Databricks

Azure AI Foundry

GenAI tooling

MLOps

CI/CD

Git

Knowledge graphs

Education

Bachelor's degree in Computer Science or related field

Tools

Claude Code

Codex

Cursor

GitHub Copilot

Copilot Studio

Job description

Downer is seeking six AI/ML Engineers to design, build and scale enterprise-grade AI solutions in an agentic-first environment. You will deploy production-grade models across Azure Databricks and Foundry, collaborating with architecture, security and data governance teams. Melbourne-based with travel to Downer sites as needed.

The role emphasizes hands-on development in Python, C#, and SQL, MLOps pipelines, and strong engineering discipline to deliver reliable, scalable AI products.