Data Infrastructure & AI Engineer

We are seeking a Data Infrastructure and AI Engineer to help advance systems at the crossroads of database engineering, artificial intelligence, and high-performance computing. In this role, you will work on challenging research and development problems spanning database internals, distributed data platforms, efficient large-language-model execution, and memory architectures for intelligent agents. You will turn concepts into working systems, assess them rigorously, and refine them into reliable, high-performing solutions. What you’ll work on * Design and implement advanced data and AI infrastructure. * Investigate database components such as query processing, optimisation, storage engines, indexing, transactions, concurrency control, recovery, and distributed data management. * Explore efficient AI techniques including LLM quantisation, on-device inference, fine-tuning, knowledge distillation, gradient-free learning, and memory for agentic AI. * Analyse workloads and conduct benchmarking, profiling, and carefully designed experiments. * Diagnose performance issues and interpret results to guide system improvements. * Collaborate on technically complex research and engineering projects, communicating findings clearly to colleagues and stakeholders. * Build and improve infrastructure for data-intensive and AI-driven applications. * Develop expertise across query execution, optimisation, storage, indexing, transactions, concurrency, recovery, and distributed data systems. * Research practical approaches to efficient AI, including model quantisation, edge inference, fine-tuning, distillation, optimisation without gradients, and agent memory. * Study real-world workloads using benchmarks, profilers, and controlled experiments. * Identify bottlenecks, investigate system behaviour, and use evidence to shape design decisions. * Contribute to demanding research and engineering initiatives while presenting technical conclusions clearly to both specialist and non-specialist audiences. What you’ll bring * A Master’s or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related discipline. * A strong foundation in areas such as computer systems, databases, AI systems, distributed systems, or operating systems. * Sound knowledge of core database-system principles. * Sound knowledge of modern AI-system principles. * Practical experience in system design, implementation, evaluation, and performance debugging. * Proficiency in at least one systems programming language, such as C, C++, Rust, or Go. * Proficiency with at least one deep-learning programming interface or environment, such as Python or TensorFlow. * Experience conducting empirical systems research through workload analysis, benchmarking, profiling, experiment design, and performance interpretation. * Strong analytical and problem-solving abilities. * The confidence to approach ambiguous, open-ended technical problems. * Clear technical communication skills and a collaborative working style. * A Master’s degree or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a closely related field. * Strong knowledge of computer systems, databases, distributed computing, AI infrastructure, operating systems, or related areas. * A solid grasp of fundamental database architecture and implementation. * A solid grasp of contemporary AI-system design and deployment. * Hands-on experience building systems, evaluating implementations, and resolving performance problems. * Fluency in one or more systems languages, including C, C++, Rust, or Go. * Experience using a deep-learning language, framework, or interface such as Python or TensorFlow. * A track record of empirical investigation involving workload characterisation, benchmarking, profiling, experimental methodology, and performance analysis. * Excellent reasoning and troubleshooting skills. * Comfort working independently on uncertain or loosely defined technical challenges. * Strong written and verbal communication, along with an effective team-oriented approach. Additional experience that would be valuable * Contributions to databases, data-processing engines, storage platforms, distributed systems, compilers, operating systems, or comparable infrastructure projects. * Knowledge of distributed, HTAP, cloud-native, vector, graph, lakehouse, or AI-native database architectures. * Familiarity with the internals of platforms such as PostgreSQL, MySQL, DuckDB, Spark, Flink, Velox, ClickHouse, RocksDB, TiDB, CockroachDB, or similar technologies. * An understanding of hardware-aware design across multi-core CPUs, NUMA, RDMA, CXL, NVM, SSDs, GPUs, NPUs, or heterogeneous computing environments. * Experience with vector search, embedding management, retrieval-augmented generation, knowledge graphs, semantic data management, or memory systems for AI agents. * Publications at leading database, systems, or AI infrastructure venues; these are welcomed but not essential. If you are an inquisitive systems engineer or researcher excited by the convergence of advanced data infrastructure and AI, apply now or email nk@eu-recruit.com *By applying to this role you understand that we may collect your personal data and store and process it on our systems. For more information please see our Privacy Notice (https://eu-recruit.com/about-us/privacy-notice/)*