This role is centred on designing and building the low-level infrastructure that powers modern databases and AI systems. Rather than integrating existing technologies, you’ll be developing the underlying components that make them work from database internals and distributed systems to performance-critical AI infrastructure.
We’re looking for engineers who enjoy working close to the hardware, solving difficult systems problems, and building scalable software from first principles.
What you’ll be working on
- Designing and implementing high-performance database and storage technologies.
- Building distributed systems, query engines, storage engines and other core infrastructure from the ground up.
- Developing AI data infrastructure, including vector search, retrieval systems and memory architectures for AI applications.
- Optimising software for maximum performance across CPUs, memory, storage and modern hardware architectures.
- Researching and prototyping new systems that improve scalability, efficiency and throughput for next-generation AI workloads.
What we’re looking for
- Strong software engineering experience in C, C++, Rust or Go.
- Background in systems programming, database internals, distributed systems, operating systems or storage engines.
- Experience designing core software components rather than integrating third-party technologies.
- Strong understanding of performance analysis, benchmarking and low-level optimisation.
- Exposure to AI infrastructure concepts such as LLM inference, vector search or RAG is beneficial.
Nice to have
- Experience contributing to systems such as PostgreSQL, DuckDB, ClickHouse, RocksDB, TiDB, Spark, Flink or similar.
- Knowledge of hardware-aware programming including NUMA, RDMA, GPUs, NPUs or CXL.
- Research, open-source or commercial experience building systems software from scratch.
