AI & Data Engineering Lead

What will your typical day look like?

You'll lead the engineering effort on client engagements – designing, building and shipping AI, data and cloud solutions, while lifting the standard of everyone around you.

Technical Direction & Architecture – Lead the technical design and implementation of your engagement, ensuring engineering decisions align with architecture, quality, security and delivery objectives .

Staying Hands-On –Maintain technical depth through critical designs, engineering decisions and reviews, staying close to the delivery challenges that matter most.

Leading Delivery – Lead engineering delivery across the engagement, removing technical blockers, maintaining delivery momentum and ensuring teams meet quality and operational standards.

Client & Stakeholder Leadership – Work directly with client stakeholders on technical direction, trade-offs and delivery risk.

Leading Engineers – Coach and develop engineers through mentoring, technical leadership and regular feedback, helping individuals grow their capability and increase their impact.

Engineering Quality & Assurance – Lead adoption of engineering practices including testing, CI/CD, code review, observability, governance and responsible AI, ensuring solutions are production-ready, supportable and aligned to engineering standards.

AI-Enabled Delivery – Drive adoption of AI-first engineering practices, reusable accelerators and modern developer tooling to improve productivity, quality and delivery outcomes.

Growing the Practice – Contribute to proposals, solution shaping and technical pursuits, while building reusable assets, accelerators and engineering patterns for the practice.

Enough about us, let's talk about you .

You may have all or some of the following skills and experiences:

6+ years' experience in software, data or AI engineering, including leading others.

Strong development skills in Python, Scala, Java or similar, plus advanced SQL, and a passion for building high-quality, maintainable solutions.

Experience designing and delivering production-grade software, data or AI solutions on modern cloud platforms such as Azure, AWS, Google Cloud, Databricks or Snowflake.

Track record of owning engineering quality through design leadership, code review, mentoring and establishment of engineering best practices.

Ability to communicate technical concepts, trade-offs and delivery risks to both technical and business stakeholders, building confidence in engineering decisions.

Ability to navigate ambiguity, break down complex problems and guide teams toward practical engineering outcomes.

Nice to have:

Experience applying AI-assisted engineering practices, agentic workflows or AI tools as part of software, data or cloud delivery.

An interest in making the value of data and AI visible to clients, through visualisation , working demos or products people actually use .

Applicants must hold working rights in Australia to apply.