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# Senior Software Engineer, Database (SmithDB)

- **Company:** Langchain, Inc
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $185,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon S3, C++ (Programming Language), Cloud Computing, Cloud Storage, Databases, Software Debugging, Distributed Data Store, Distributed Systems, Memory Management, Open Source Technology, Software Engineering, Database Engines, System Programming, Indexer, Juniper, Kubernetes, Low Latency
- **Published:** November 6, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-database-smithdb-san-francisco-ca--6e71d8b6-d06e-4327-b264-be0e4c7c57b3

## About the Role

Software Engineering, Artificial Intelligence (AI) Agents, Prototyping, Software Agents, Open Source, Product Development, Benchmarking, Juniper Networks M-Series, LinkedIn, Fortune 500 Customers, * 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 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)