About this role
What you will do:
You’ll work closely with researchers, infrastructure engineers and application specialists, helping bridge the gap between research and production.
Your work will include:
- Designing and building core components of the company's software platform
- Developing backend services, APIs and supporting infrastructure
- Contributing to algorithms and the implementation of novel AI capabilities
- Translating research concepts and prototypes into maintainable, production-ready software
- Designing systems capable of handling large-scale reasoning and inference workloads
- Working with concurrent, parallel and distributed systems
- Making architectural decisions around performance, reliability and scalability
- Writing well-tested, maintainable code and contributing to engineering standards
- Participating in code reviews and technical design discussions
- Helping shape how AI-assisted development tools are used across the engineering organisation
What you will need:
- A Master's degree in Computer Science, Computer Engineering or a related technical field, or equivalent practical experience
- Strong professional software engineering experience, with evidence of taking significant technical ownership
- Excellent proficiency in at least one modern programming language — examples include Rust, Elixir, Python, C, Java, F#, Haskell or similar
- Strong foundations in software design, including both functional and object-oriented approaches
- Experience designing and building concurrent, parallel or distributed systems
- Experience working with a major cloud platform such as AWS, Google Cloud or Azure
- A strong interest in software architecture, algorithms and solving technically challenging problems
- Hands-on experience with modern AI coding assistants such as Claude or Codex
Nice-to-haves:
- Experience with AI, machine learning or scientific computing
- Experience working on inference, optimisation or other computationally intensive workloads
- Previous experience in an early-stage startup
- Experience working effectively in a distributed or remote engineering environment
- DevOps / platform engineering experience
- Experience taking research or experimental software and turning it into reliable production systems