AI Data Platform Engineer — GenAI & Agentic AI

Compare the Market Australia

Brisbane

On-site

AUD 140,000 - 190,000

Full time

10 days ago

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Benefits offered by this job

Flexible work arrangements

Annual celebrations & events

Volunteer Day leave

Free coffee on Mondays

Leave purchase options

Return To Work bonus

Quarterly awards program

Job summary

Compare the Market Australia (iSelect and CTM brands) is seeking an AI Data Engineer to design and deliver AI‑enabled data platform capabilities. You will build scalable, secure foundations to accelerate agentic AI adoption across the enterprise.

You will work across cloud‑based data platforms to develop AI‑driven infrastructure, automation, and services supporting ML, Generative AI, and advanced analytics for better data discovery and decision making.

Qualifications

4+ years' experience in Gen AI Engineering, Data Engineering, Integration Engineering, Data Science, Software Engineering, or related disciplines, delivering enterprise‑scale solutions from concept through to commercial deployment
Proven experience in designing, developing, deploying, monitoring, and optimising raw models, including model training, fine‑tuning, evaluation, versioning, experiment tracking, observability, drift detection, and token usage management
Strong expertise in Generative or Agentic AI engineering patterns, including Retrieval‑Augmented Generation (RAG), semantic search, vector search, embeddings, prompt engineering, context management, AI agents, tool calling, and multi‑agent architectures
Experience building agent powered applications and intelligent automation solutions, including enterprise copilots, chatbots, knowledge assistants, research agents, workflow automation, and decision‑support capabilities
Hands‑on experience with modern frameworks and platforms, including PyTorch, TensorFlow, Scikit‑Learn, Hugging Face, LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, and Microsoft Copilot Studio
Experience with AI‑driven data solutions on EDPs, knowledge repositories, feature stores, vector databases, and data products using cloud‑native Data platforms such as Databricks, Snowflake, Fabric, Synapse, Redshift, BigQuery, AWS, Azure, or GCP
Experience operationalising agent solutions using MLOps and LLMOps practices, including MLflow, Databricks ML, SageMaker, Bedrock, AI Foundry, Vertex AI, containerisation, and deployment automation
Strong understanding of AI governance, security, and Responsible AI principles, including data privacy, data sovereignty, model governance, access controls, metadata management, lineage, compliance, and optimisation of model performance, scalability, latency, and cost efficiency

Responsibilities

Design, develop, and implement AI‑driven data solutions and agent‑based products on the EDW that support model learning, generative AI, intelligent automation, and advanced analytics for better data discovery
Develop, deploy, and operationalise foundational models, LLMs, RAG, semantic search, vector retrieval, embeddings, and enterprise knowledge management capabilities
Design and implement intelligent automation and agentic AI solutions leveraging AI agents, orchestration frameworks, multi‑agent architectures, workflow automation, and reusable AI services and APIs
Establish and champion AI engineering best practices including MLOps, LLMOps, model monitoring, query observability, experiment tracking, benchmarking and token usage management
Drive AI innovation, platform optimisation, and governance by evaluating emerging technologies, improving model performance and cost efficiency, and ensuring compliance with security, privacy, data governance, and Responsible AI standards