Build AI systems. Automate the boring stuff. Work with interesting data. Ship things people actually use.
A growing, data-driven organisation is expanding its Data & AI capability and is looking for a
hands-on Data & AI Builder
to join the team.
This is a role for someone who enjoys figuring things out, building quickly and turning ideas into working production systems.
It's
not a traditional data science role
. You won't be spending your days training custom ML models.
It's also not an architecture role where you spend your time drawing diagrams.
We're looking for someone who can
write the code, build the workflow, integrate the APIs and ship the solution.
The Role
The role sits roughly
***** between AI/LLM engineering and data engineering
, with the balance shifting depending on what's happening across the business.
On the data side, you'll work across modern cloud data infrastructure, pipelines and large-scale datasets.
On the AI side, the focus is predominantly on
automation and integration rather than building models from scratch
.
Think roughly
70% automation/integration and 30% model-focused work
.
You'll work with technologies such as:
LLM APIs including
Claude, Gemini and VAPI
n8n
and other workflow automation tools
Databricks and Azure
Python and SQL
APIs, webhooks and event-driven workflows
RAG and prompt engineering
LLM evaluation
One day you could be building a Databricks notebook. The next, you might be debugging an n8n webhook or integrating an LLM into a production workflow.
What You'll Be Working On
There are multiple AI and data initiatives underway, giving you the opportunity to work across a broad range of problems.
You'll be involved in building and improving:
AI-powered workflows and automation
LLM-based applications and integrations
Data pipelines and processing systems
Automated QA and assessment tooling
Voice and conversational AI applications




Modern Databricks and Azure infrastructure
Internal tools and lightweight data products
Integrations between APIs, platforms and internal systems
There's plenty of opportunity to move from
early-stage POC through to production
, rather than simply handing ideas over to another team.
What You'll Actually Do
GenAI & Automation
Build and ship AI-powered workflows, agents and automation
Integrate LLM APIs into real production workflows
Develop automation using tools such as
n8n
Work with APIs, webhooks and event-driven pipelines
Prompt, evaluate and iterate LLM-based systems
Build RAG-style solutions and AI-powered applications
Integrate voice AI and other third-party AI services
Build and maintain data pipelines across multiple markets and data sources
Work with
Databricks, Azure and modern cloud data platforms
Develop ingestion, transformation and data processing workflows
Work with structured and unstructured datasets
Build reliable, observable and maintainable data systems
Contribute to the evolution of the underlying data infrastructure
Product & Building
Build lightweight internal tools and dashboards
Integrate third-party platforms and services
Turn rough business requirements into working products
Prototype quickly and iterate based on what you learn
Take ownership of problems rather than waiting for someone else to tell you how to solve them
What We're Looking For
This is a
hands-on role
.
You'll get plenty of technical direction from senior engineers and team leads,



so we're not looking for someone who wants to spend their time defining enterprise architecture.
We're looking for someone who can
independently take a problem and build something useful
.
The Kind of Person We're Looking For:
You build things because you're curious.
You've got side projects, experiments, prototypes or tools you've built because you thought "surely this could be automated."
You use AI in your day-to-day work.
You're already experimenting with AI-native tooling and looking for ways to make yourself and your team more productive.
You have a bias towards action.
You don't need a perfect requirements document before you start. You can assess a problem, make a sensible call and start building.
You can work independently.
You'll have technical support around you, but you won't need to be managed closely.
You know when to ship.
You understand the difference between something that needs more engineering and something that's good enough to get into the hands of users and learn from.
You have no ego.
Titles aren't important. Valuable ideas are. You should be comfortable challenging ideas, receiving feedback and changing your mind when someone has a better approach.
Why This Role?
Work on
real production AI
, not just experiments and demos
Work with
LLMs, voice AI and automation
Get hands-on with
Databricks and modern data infrastructure
Work across AI, data engineering, automation and product
Have genuine ownership from day one
Build solutions that have a direct business impact
Work in a fast-moving environment where curiosity and getting things shipped are valued
Show Us What You've Built
We care much more about
what you can actually build
than what your CV says.
If you've got a GitHub repo, working demo, side project, Loom walkthrough or something you've built because you couldn't stop thinking about the problem — we'd love to see it.

📌 Artificial Intelligence Engineer (New South Wales)
🏢 Talent Insights Group
📍 New South Wales