Senior Backend Engineer

Orbital Industries is an AI Industrial company, with frontier AI embedded at every step in the production of critical physical products - from creating advanced materials to engineering and manufacturing.

Every Orbital Industries product is developed using CurieOS, our AI operating system, uniting AI-automated hardware engineering with AI-designed material science to achieve breakthrough real-world performance. We also offer CurieOS to our customers and partners, extending the same platform and workflows that power Orbital Industries to their own teams and products.

We have an ambitious mission and need excellent people in all our teams - AI research, operations, advanced materials, mechanical engineering, chemical engineering and manufacturing.

Working at Orbital Industries means working in vertically integrated teams across the full stack, from molecules to manufacturing. We're looking for people who have a love of physical technology, curiosity in AI and a desire to learn.

Orbital's AI software platform, CurieOS, is used by scientists and engineers to design and build products serving critical industries. Powering this software are our world leading AI models in advanced materials, hardware engineering and simulation.

As a Backend Engineer at Orbital you will design, build and operate the core systems powering CurieOS. You will work across the full backend stack: APIs, data pipelines, graph databases, event-driven architectures and the infrastructure that connects our AI models to the tools our scientists and engineers use daily. An example of a feature you might build is a unified context graph across materials, engineering and manufacturing data for our AI agents.

First and foremost, we want to work with someone with a love of craftsmanship, continual learning and building systems that scale.

Build and operate core backend systems

• Design and implement APIs, services and data pipelines that power CurieOS, with a focus on reliability, performance and clean abstractions

• Build and maintain integrations between our AI models, scientific tools and internal workflows

• Own the full lifecycle of backend features from design through deployment, monitoring and iteration

Drive engineering quality

• Write well-tested, maintainable code and contribute to a culture of high engineering standards through code review, documentation and technical discussion

• Improve system observability, reliability and performance — instrument, monitor and optimise the systems you build

• Make pragmatic technical decisions that balance speed of delivery with long-term maintainability

Collaborate across the team

• Work closely with ML researchers, product engineers and domain experts (materials scientists, hardware engineers) to understand their needs and translate them into robust backend solutions

• Contribute to architectural decisions and help shape the technical direction of the platform

• Share knowledge, mentor peers and help establish best practices as the team grows

• Backend engineering experience with strong programming skills

• Proven experience designing, building and operating backend systems in production — APIs, data pipelines, event-driven architectures or similar

• Strong fundamentals in at least one backend language (e.g. Python, Go, Rust, Java/Kotlin) and comfort working across the stack when needed

• Experience with databases (relational and/or graph), message queues, caching layers and cloud infrastructure

• A track record of shipping and iterating on software that real users depend on, with a strong sense of what makes systems reliable and maintainable

• The ability to reason about system design, data modelling and engineering trade-offs — and to communicate these effectively

• An ability to debug…