orbitalindustries - Senior Backend Engineer
Requirements
• 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 complex distributed systems through meticulous attention to detail, structured investigation and carefully chosen instrumentation • A genuine interest in building software that enables breakthrough scientific and industrial applications • Upon reading Hamming's You and Your Research, you resonate with quotes such as: • "Yes, I would like to do first-class work" • "You should do your job in such a fashion that others can build on top of it, so they will indeed say, 'Yes, I've stood on so and so's shoulders and I saw further.'" • "Instead of attacking isolated problems, I made the resolution that I would never again solve an isolated problem except as characteristic of a class" • Bonus: Previous experience working in an AI/ML environment, familiarity with the workflows, tooling and pace of AI teams is a real advantage. Experience with graph databases, knowledge graphs or scientific data platforms. Experience with infrastructure-as-code, containerisation (Docker/Kubernetes) or CI/CD pipelines.
Responsibilities
• Build and operate core backend systems • Design and implement APIs, services and data pipelines that power the Curie platform, 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
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