Designs, optimizes, and scales a distributed database storage layer for AI observability using Rust. Engineers performant ingestion/query code, integrates with cloud storage, deploys on Kubernetes, and profiles for cost/speed. Requires 5+ years systems/database experience, Rust proficiency.
175k – 240k/yr
On-site5+ YOEBackend Engineering
About the role
What you'll do
Engineer performant Rust code for ingestion and query execution
Optimize for cost and speed, heavily utilizing memory and CPU profiling
Integrate tightly with cloud object stores (S3/GCS/Azure Blob)
Deploy our distributed database services on Kubernetes (multi-tenant, high throughput, low latency)
Contribute to observability for the storage engine itself (metrics, tracing, debug tooling)
What you'll bring
5+ years in systems/database engineering with strong experience in a systems programming language (Rust, C++). Rust strongly preferred, as it is the language we use.
Knowledge of database internals is a plus: query engines, storage systems, indexing, and compaction
Proficiency in systems performance analysis: memory allocation, CPU hotspots, lock contention, async runtimes.
Familiarity with similar query execution engines is a plus
Experience with Kubernetes, distributed systems, and cloud object storage is a plus.
Strong fundamentals in networking, OS concepts, and systems debugging.
Designs and develops ultra-low-latency high-frequency trading infrastructure in C++ and Linux. Optimizes performance across hardware/software layers and collaborates with quants for trading systems impact.
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