When the rest of the world is headed left, Ethan goes right. We’re more than an IT, telco, and cloud provider, we’re disruptors and game-changers—we’re the kids in the class always doodling, creating, and innovating. Can you relate?

This is more than an AI/ML Engineer role. We’re looking for someone who’ll embrace our ethos and help shape the future of our industry. You won’t just build prototypes – you’ll ship models, agents and AI applications to production, running on open models and sovereign infrastructure both our customers and our internal operations.

You’ll also live and breathe our 10 commandments* (see More Than an Appendix below).

MORE THAN A ROLE

Our role descriptions aren’t the norm. Your key responsibilities in the role are:

- Model building and right-sizing

- Select, test and fine-tune open-weight and commercial models (LoRA, QLoRA, distillation, quantisation).
- Prepare training data with Data Engineers and right-size models for accuracy, latency and cost.

- Agents and AI applications

- Build RAG pipelines and single/multi-agent workflows with tool use and MCP.
- Implement guardrails and integrate with client systems, data and identity.

- Evaluation and quality

- Automate accuracy, groundedness, safety and bias testing on every change.
- Report honestly against agreed success criteria.

- Production readiness and operations

- Deploy models and apps with Docker, Kubernetes, vLLM/Triton and CI/CD.
- Meet observability and run-readiness standards, then hand over and support early-life issues.

- AI observability and DevOps

- Instrument models, RAG and agents with OpenTelemetry, feeding Ethan-A observability and ServiceNow.
- Monitor quality, drift, SLOs, cost and capacity,



with full agent audit trails.
- Release safely (Terraform, Helm, GitOps, canary) and support SRE on AI incidents.

- Proofs of concept and internal use cases

- Rapidly build POCs with the Principal AI Architect and AI tools for Ethan Global service delivery.
- Contribute reusable accelerators and templates.

- Engineering practice

- Follow coding, testing and security standards, keeping client data in sovereign environments.
- Work as one team with vendor-panel engineers.

THE ABSOLUTES-MUSTS
- Degree in computer science, engineering, mathematics or a related field, or equivalent experience.
- Previous experience in software or Machine Learning engineering, including working knowledge of deep learning or LLMs.
- Experience deploying at least one model or AI application into production.
- Hands-on model fine-tuning and evaluation experience.
- Experience building RAG or agent solutions integrated with enterprise systems.
- Experience working in agile teams using code reviews and CI/CD.
- Experience instrumenting and supporting production services, including monitoring, alerting and incident response.

CERTS AND SKILLS

Don’t walk in empty-handed. We want to see any of these (not essential):
- Strong Python and PyTorch; writes clean, tested code
- Hyperscaler machine learning or AI engineer certification or




- NVIDIA-Certified Professional: Generative AI LLMs (NCP-GENL).

Think you can fit more than a mould? Reach out, get in contact, arrest us with your professional rap sheet. Did we mention we’re looking for diversity? If you’re Aboriginal or Torres Strait Islander, we’d strongly advise you to apply.

MORE THAN AN APPENDIX (IT’S A LIFESTYLE)

1. Professionalism and poise: Maintaining a dignified and professional demeanour across all interactions.
2. Client-centric excellence: Delivering results that prioritise our clients’ needs and ensuring their end-to-end journey is nothing short of exceptional.
3. Elevating the company’s success (not just your own): Understanding that we all win together.
4. Extraordinary dedication: An eagerness to go beyond industry standards and expectations.
5. Innovative mindset: A natural inclination to think creatively and a desire to collaborate with others who share this same perspective.
6. Adaptive agility: Being versatile and responsive to the ever-changing technology landscape.
7. A commitment to crafting recent realities: Cultivating opportunities and creating positive experiences between colleagues, clients, and everyone you encounter.
8. Continuous learning: An insatiable appetite for knowledge and skill enhancement, ensuring you’re always at the forefront of your field.
9. Empathetic engagement: Building strong, genuine connections with clients and team members by putting in the time to understand their perspectives and needs.
10. Sustainability awareness: A consciousness about the impact of our actions on the environment and society, aiming for sustainable business practices.

📌 AI Engineer (Sydney)
🏢 Ethan
📍 Sydney