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# Software Engineer, SmithDB

- **Company:** Langchain Inc.
- **Location:** United States
- **Experience:** Expert
- **Salary:** $175,000.0 - $240,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon S3, Systems Engineering, C++ (Programming Language), Cloud Computing, Cloud Storage, Databases, Software Debugging, Distributed Data Store, Distributed Systems, Memory Management, Database Engines, System Programming, Indexer, Kubernetes, Low Latency
- **Published:** May 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6625955683842f9a

## About the Role

Do you have experience in Systems engineering?, * 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.

## Description

We're building a storage layer specifically designed for AI observability and evaluation. We're a fast-moving team looking for a systems / database engineer to help design, optimize, and harden our system. Within 6 months, we've gone from idea to production system but there is still lots to build and optimize. You'll be working on execution, storage layout, performance profiling, and scaling to trillions of traces. This role is based in San Francisco.

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)


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