Firmus Technologies

Firmus Technologies is a global leader pioneering the development and operation of efficient AI infrastructure across Asia Pacific.

Founded in Australia in 2019, our mission is to create the most efficient AI infrastructure by combining cutting-edge technology with a steadfast commitment to sustainability.

At Firmus, we are unique in our approach. We design, build, and operate a new class of digital infrastructure – the AI Factory. Through our model-to-grid technology approach, we have pushed the boundaries of multi-generational liquid cooling systems, energy management, AI software orchestration, and construction. For our customers, this approach allows us to make every watt count and deliver low-cost AI tokens globally.

Firmus AI Cloud

Our large-scale GPU cloud platform, Firmus AI Cloud, is purpose-built to deliver energy-efficient AI compute at scale to customers.

It empowers developers, enterprises, educational institutions, and government users to train and deploy AI models with unmatched efficiency and cost savings. With an ever-growing suite of services and applications, we are committed to delivering a cloud experience that is market-leading, proprietary, and built to scale.

Why Firmus?

As an NVIDIA Cloud and Engineering partner in Asia Pacific, you will gain skills, experience, and exposure across the AI industry and be part of shaping what this industry looks like for decades to come.

We are founder-led, not a big corporate. Decisions happen fast, our leaders are accessible, and there's minimum bureaucracy between you and the work. Ownership comes early. Whatever your role, you will have a direct line to outcomes, helping shape how the business grows as we scale nationally across a long-term, large-scale roadmap.

Work alongside founders and experts in AI infrastructure, energy systems and next-generation compute.

What we build here has impact beyond the business. Our AI Factories are designed to operate as assets to the energy grid to actively strengthen the communities and regions they operate in rather than drawing from them.

Considering applying? You don't need a perfect background to join our team. If you're driven and curious, there's a path for you. We back our people to grow into new domains and take on challenges beyond their previous experience.

ROLE SUMMARY

This is a Head of role in the Technology division, leading the engineering function that owns the architecture, engineering and delivery of AIFactoryX. AIFactoryX is Firmus’s simulation and optimisation platform and the digital twin of every Firmus AI Factory. It lets us test a complete AI factory as one system, covering compute, network, cooling, electrical, energy supply and economics, before we commit capital, and then keeps learning from how the factory actually performs through commissioning and operation.

The job is systems engineering and platform architecture, not visualisation. What AIFactoryX produces is a reproducible, evidence-backed answer to a consequential question: which platform, which cooling architecture, which site, and how much useful compute we get per megawatt. A 3D model or a dashboard is a way of showing that answer, not the answer itself. AIFactoryX informs design, build and operating decisions, while live operations and control stay with AIFactoryOS.

You’ll start with an existing team of CFD and Omniverse engineers and partner specialists, and grow it into a multidisciplinary function spanning platform, simulation, data and applied-AI engineering. You’ll work closely with AI Factory Development, AI Platforms, Energy and Finance, and the twin’s results will be the evidence Firmus relies on when deciding whether a design, build or site is ready to move forward.

KEY RESPONSIBILITIES

Own the AIFactoryX architecture and roadmap across every layer of the factory. That covers the physical plant (thermal and CFD, liquid cooling, electrical and mechanical), the compute layer (NVIDIA platforms, rack and network topology, workload behaviour) and the energy and commercial layer (grid connection, tariffs and project economics). Design it so one platform can model any site, climate, grid, tariff or NVIDIA platform through versioned configurations, rather than a new copy for every factory.

Run the engineering pipeline that takes the design master through a common CAD model into CFD, electrical studies and NVIDIA Omniverse. Omniverse and OpenUSD are how people see and explore the factory, while the specialist solvers remain the authority on their own numbers. Keep the models in step with the live design so they don’t quietly drift apart.

Set the fidelity framework that decides how much detail each model needs and how far it can be trusted. Every model should state its level of detail, what it has been calibrated against, how uncertain it is and which decisions it can support. Lead calibration against commissioning data and measured AIFactoryOS telemetry, use physics-ML surrogates where they genuinely earn their place, and keep the platform focused on useful compute per watt across the whole factory rather than a cooling number on its own.

Turn the platform into decisions across the life of a factory: optimising designs and choosing sites, producing a Basis of Design traceable to its evidence, rehearsing management software and failure recovery before equipment arrives, planning operational changes and working out what went wrong after an incident.

Own delivery. Run a steady weekly rhythm, make sure the team has the compute, licences and tools it needs, and manage the budget for them, working with IT and AI Infrastructure so engineers aren’t left waiting. Prove the approach on one site and one Hypercube first, then extend it across the portfolio.

Own the engineering standards, including software quality, reproducible results, data lineage, security and keeping private operating and customer data where it belongs. Build and lead the team, manage the relationships with NVIDIA, solver vendors and engineering partners, and keep the CTO informed on progress, how much confidence the models deserve and the main risks.

SKILLS AND EXPERIENCE

You’ll bring 12–15+ years across systems engineering, simulation or computational engineering and large-scale software platforms, with a degree in engineering, physics, applied mathematics or a close discipline. You’ll have led a team that built production simulation or digital twin platforms whose results were used to make real engineering, operating or investment decisions, not demos. You’ll have designed the interfaces and data models other engineers build on, and you’ll have a strong systems-engineering foundation in requirements, trade studies, verification and validation, applied to complex physical systems such as data centres, power systems, process plants, aerospace or semiconductors.

You’ll have depth in at least one engineering or simulation discipline, such as thermal and cooling, electrical, or compute and network modelling, and the curiosity to learn the rest. You understand how models are validated and where they stop being reliable, and you’re comfortable reading and reviewing code. Experience in AI or HPC infrastructure, NVIDIA Omniverse and DSX, or industrial digital twins in high-availability environments is highly valued.

LOCATION

Reporting directly to the CTO. Based in Singapore or Australia, with travel to Firmus AI Factory sites and partner engineering teams as required.

Employment Basis

Permanent full-time

Diversity

At Firmus, we are committed to building a diverse and inclusive workplace. We encourage applications from candidates of all backgrounds who are passionate about creating a more sustainable future through innovative engineering solutions.

Join us in our mission to revolutionise the AI industry through sustainable practices and cutting-edge engineering. Apply now to be part of shaping the future of sustainable AI infrastructure.