abra R&D is looking for a Senior Embedded Engineer!
abra R&D is looking for an Embedded Engineer to help build the first real-time database purpose-built for AI agents at scale. Designed around time-series and unstructured data, it leverages a custom storage format optimized for append-heavy, real-time workloads.
Joining the team means working on a high-performance execution engine built with vectorized execution, SIMD, and cache-efficient memory layouts, enabling extreme low-latency and high-throughput performance at scale.
The system is engineered to fully utilize modern hardware, with deep optimization across CPU cache layers (L1 / L2 / L3), pushing the limits of real-time data processing.
What You’ll Do
- Design and implement core components of the database engine (query engine, execution engine, storage engine)
- Build vectorized execution pipelines optimized for SIMD
- Design and evolve a time-series optimized storage engine (custom on-disk + in-memory formats)
- Work on unstructured / event-driven data representations and efficient indexing/querying strategies
- Own memory layout, compression, and data defragmentation
- Develop cache-aware / cache-efficient data structures with deep understanding of CPU cache behavior
- Implement distributed data primitives: sharding, partitioning, replication, and data locality
- Profile and optimize performance at the CPU level (cache misses, branch prediction, memory bandwidth)
Requirements:
- 7+ years of experience in high-performance systems programming (C/C++)
- Deep understanding of computer architecture (CPU pipelines, cache hierarchies, memory access patterns)
- Strong experience with low-level optimization and profiling tools
- Proven knowledge of multithreaded development (lock and lockfree)
- Expertise in algorithms and data structures, especially cache-aware designs
- Experience in one or more of the following:
- Database internals (query engines, storage engines, query planners/optimizers)
- Time-series or real-time data systems
- High-performance systems (trading systems, game engines, networking stacks, compilers)
- Distributed systems (sharding, partitioning, consistency models)
Strong Plus
- Experience with vectorized execution engines (e.g., DuckDB-style processing)
- Experience designing custom storage formats or low-level data layouts
- Experience handling unstructured or semi-structured data at scale
- Background in query optimization and execution planning