Database Research Engineer

European Tech Recruit; City of Edinburgh; On-site; GBP 85,000 - 120,000; Full time

Job summary

European Tech Recruit in Edinburgh is seeking Researchers and Engineers to join a leading deep-tech group focused on agent-native data management and AI data infrastructure. You will work on database kernels, query processing, storage engines, and distributed systems, translating research into scalable real-world systems.

The role blends research with hands-on system design, benchmarking and performance optimisation, tackling AI agents, vector search, RAG, semantic data management, and

Qualifications

• 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.

Responsibilities

• Design, implement, evaluate and performance-debug database and AI data infrastructure components.
• Collaborate across research and production engineering to translate research into scalable systems.

Skills

C

C++

Rust

Go

Benchmarking

Profiling

Workload analysis

Performance optimisation

Distributed databases

Systems design

Education

Master's or PhD in Computer Science or Computer Engineering

Tools

PostgreSQL

MySQL

DuckDB

Spark

Flink

Velox

ClickHouse

RocksDB

TiDB

Job description

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