At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.
With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.
Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.
About the team
SmithDB is LangChain's internal database team. We're building a storage and query layer purpose-built for AI observability and evaluation. Within six months we went from idea to a production system that offers industry leading performance and scalability for agent observability data. We're a small, fast team of systems engineers tackling genuinely hard problems: storage layout, query execution, compaction, and scaling toward trillions of agenbt traces. We develop in Rust, run on Kubernetes, and integrate tightly with S3/GCS/Azure Blob. There are no legacy constraints; this is a greenfield system with real production load and ambitious engineering goals.
About the role
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)
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.
Compensation
Salary Range: $175,000-$240,000 USD
Compensation Philosophy:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BenefitsBenefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.