AI engineer

Build the AI systems that power critical infrastructure across millions of customers.

You'll design and deploy machine learning solutions that directly impact essential services. Working with Databricks and Azure, you'll create everything from predictive maintenance models to intelligent automation tools. You'll also mentor engineers and establish AI frameworks that guide enterprise-wide adoption.

You'll work with modern tools throughout. Databricks handles your ML experimentation and deployment. Azure provides the cloud foundation. Python and TypeScript power your development work. The team values technical depth over politics, and you'll have genuine autonomy to architect solutions properly.

This is a leadership role where your technical decisions shape strategy. You'll work directly with business stakeholders to understand real problems, then build the AI systems that solve them. The company invests in proper tooling and gives you time to do things right rather than rushing to market with half-built solutions.

What You'll Do

• Build and deploy ML models using Databricks, MLflow, and Azure AI services for production systems
• Design AI applications like chatbots and automation tools that integrate with existing enterprise workflows
• Establish MLOps practices and AI governance frameworks across the organisation
• Mentor data scientists and engineers while collaborating with architects on technical strategy

What You'll Need

• 5+ years with Databricks ML, MLflow, Delta Lake, and Spark for large-scale data processing
• Advanced Python and TypeScript skills with 10+ years software or data engineering experience
• Strong MLOps experience including model deployment, monitoring, and CI/CD pipeline management
• Experience with Azure cloud services, LLM fine-tuning, and AI orchestration frameworks like LangChain

About the Company

They're a major utility company serving millions of customers across essential water and sewerage services. The organisation is modernising its data and AI capabilities with proper investment in tools, training, and technical leadership positions.

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