AI Engineer
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Description
AI Engineer
Sydney | Hybrid | Permanent
We're working with a technology-led organisation investing heavily in modern engineering capability and applied AI to improve how teams build, operate, and scale digital solutions and enabled with wider business.
This is an opportunity to join a high-performing engineering team focused on building intelligent systems that integrate into a broader cloud and platform environment. You'll be working closely with an experienced Engineering Manager and contributing to real-world AI initiatives that drive business outcomes.
The Role
You'll sit within a modern engineering team delivering AI-enabled solutions across a cloud-native environment. This is a hands-on role suited to someone with a strong development background who enjoys building, shipping, and iterating on production-grade systems.
You'll work across the full lifecycle - from problem definition through to deployment - with a focus on pragmatic, scalable solutions rather than experimentation for its own sake.
What You'll Be Doing
- Build and deploy AI-driven applications and services in a production environment
- Develop scalable backend systems using Python
- Work across AWS to design, build, and operate cloud-native solutions
- Deploy and manage workloads in Kubernetes-based environments
- Collaborate with engineers, product, and business stakeholders to deliver practical AI use cases
- Contribute to the design and evolution of internal platforms and tooling
- Translate business problems into technical solutions using a mix of software engineering and AI approaches
- Support continuous improvement across engineering practices, tooling, and delivery
What We're Looking For
- Strong software engineering background (ideally backend-focused)
- Commercial experience building applications in Python
- Hands-on experience with AWS (compute, storage, networking fundamentals)
- Experience working with Kubernetes or containerised environments
- Exposure to AI/ML concepts or experience building AI-enabled features (LLMs, automation, data-driven systems, etc.)
- Ability to work in evolving environments where requirements aren't always fully defined
- Strong problem-solving skills and a pragmatic approach to delivery
- Comfortable collaborating across technical and non-technical stakeholders
Why Consider This Role?
- Work on applied AI initiatives that are actually used in production
- Strong engineering leadership and mentorship
- Modern cloud and platform environment (AWS + Kubernetes)
- Opportunity to shape how AI is integrated into broader engineering systems
- Collaborative, delivery-focused culture