IT & Software

Database Research Engineer

European Tech Recruit

City Of Edinburgh · Scotland · United Kingdom

Agent-Native Database Systems Research / Engineer

Location: Edinburgh, UK | Full-time

A leading deep-tech research and engineering organisation is looking for Researchers and Engineers to work on next-generation database and AI data infrastructure, with a particular focus on agent-native data management, database kernels, query processing, storage engines, distributed systems, and AI workloads .

This is an opportunity to work at the intersection of database systems, AI, cloud infrastructure, and hardware acceleration , combining research with hands-on system design, prototyping, benchmarking, and performance optimisation.

You’ll tackle open-ended technical problems around AI agents, vector search, RAG, agent memory, semantic data management, distributed databases, and high-performance query processing , with the opportunity to translate research into real-world data infrastructure.

Ideal candidates will have:

  • Master's or PhD in Computer Science, Computer Engineering , or a related discipline
  • Strong background in database systems, computer systems, distributed systems, AI systems, or operating systems
  • Solid understanding of database internals including query optimisation, query execution, storage engines, indexing, transactions, concurrency, and recovery
  • Hands-on experience designing, implementing, evaluating, and performance-debugging systems
  • Strong programming skills in C, C++, Rust, or Go
  • Experience with benchmarking, profiling, workload analysis, and performance optimisation
  • Ability to conduct empirical systems research and solve open-ended technical problems
  • Strong technical communication and collaborative skills

Preferred Qualifications:

  • Experience with PostgreSQL, MySQL, DuckDB, Spark, Flink, Velox, ClickHouse, RocksDB, TiDB , or similar systems
  • Knowledge of distributed, cloud-native, HTAP, vector, graph, lakehouse, or AI-native databases
  • Experience with AI data infrastructure , including vector search, embeddings, RAG, knowledge graphs, semantic data, or agent memory
  • Understanding of hardware-aware system design across multi-core CPUs, NUMA, RDMA, CXL, NVM, SSDs, GPUs, and NPUs
  • Experience with storage engines, compilers, operating systems, or other low-level infrastructure
  • Publications in venues such as SIGMOD, VLDB, ICDE, CIDR, EuroSys, OSDI, SOSP, or NSDI
  • Experience working across research and production engineering environments

Key Words:

Database Systems / Database Engineer / Database Researcher / Systems Researcher / Research Engineer / AI Infrastructure / AI Data Infrastructure / Agent-Native Systems / Agent Memory / Vector Database / Vector Search / RAG / Knowledge Graph / Semantic Data / Query Optimisation / Query Execution / Query Processing / Database Kernel / Storage Engine / Indexing / Distributed Databases / Cloud-Native Databases / HTAP / Lakehouse / Transaction Processing / Concurrency Control / C / C++ / Rust / Go / PostgreSQL / DuckDB / Spark / Flink / Velox / ClickHouse / RocksDB / TiDB / NUMA / RDMA / CXL / GPU / NPU / Performance Optimisation / Benchmarking / Profiling / SIGMOD / VLDB / ICDE / EuroSys / OSDI / SOSP / NSDI / Edinburgh

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Reference: WJ-766_21964610

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