LangChain

ABOUT US 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 agent 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 building a database specifically designed for AI observability and evaluation, and we need someone to own the infrastructure layer that keeps it running reliably at scale. As a Database Infra Engineer on the SmithDB team, you won't be designing the storage engine — you'll be making sure the engine never goes down, scales seamlessly as our customer base grows, and is operationally excellent across cloud environments. What you'll do - Own the deployment and operations of SmithDB across cloud environments — including cluster lifecycle management, blue/green and rolling upgrades, and automated failover - Build and maintain the infrastructure tooling (Terraform, Kubernetes, Helm, or equivalent) that provisions, configures, and scales SmithDB nodes - Own the Kubernetes infrastructure that runs our distributed database services (multi-tenant, high throughput, low latency) - Build and improve deployment pipelines, rollout strategies, and infrastructure-as-code for the storage layer - Drive reliability engineering efforts: incident response, postmortems, SLOs, and disaster recovery for a system operating at massive scale - Manage capacity planning and cost efficiency — model growth, rightsize resources, and ensure SmithDB can absorb traffic spikes from our largest customers without manual intervention - Build the CI/CD pipeline for database infrastructure changes — safe, tested, and fast promotion from dev through staging to production - Collaborate closely with SmithDB internals engineers to translate new engine features into production-ready infrastructure changes and ensure safe, low-risk rollouts What you'll bring - 5+ years of experience in infrastructure, platform engineering, or SRE with hands-on - Strong hands-on experience with Kubernetes and cloud infrastructure (AWS/GCP/Azure) - Solid scripting/systems programming ability (Go, Python, or similar); - Experience with infrastructure-as-code and CI/CD tooling (Terraform, Helm, ArgoCD, or similar) - Deep familiarity with at least one major cloud provider (AWS, GCP, or Azure) and the primitives used to run stateful workloads reliably — persistent volumes, managed node groups, cloud storage, etc. - Infrastructure-as-code fluency — you write Terraform (or Pulumi/CDK) as your primary language, not an afterthought - Strong operational instincts — you've been on-call for high-traffic data systems, you know how to triage under pressure, and you write runbooks that actually get used - Experience with container orchestration (Kubernetes) and deploying stateful workloads in production - A bias for automation — if you've done something manual twice, you're already thinking about how to make it never happen again - Strong written and oral communication skills, with the ability to translate infrastructure health into language product and business stakeholders understand - The DNA to thrive in a fast-moving, high-autonomy environment — you see gaps as opportunities and own them end to end Nice to Have - Ownership of production database systems (Postgres, ClickHouse, Redis, or similar) - Comfort reading and reasoning about Rust is a plus, as it's the language our database is written in - Understanding of database reliability concepts — replication, backups, point-in-time recovery, connection pooling, and graceful degradation under load Compensation Salary Range: $180,000-$230,000 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. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

ABOUT US 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 agent 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 looking for a hands-on Engineering Manager to lead the SmithDB team. This is not a pure people-management role. You'll write production code, review PRs at the systems level, make architectural calls, and be in the weeds alongside your engineers. At the same time, you'll own team health, hiring, technical roadmap, and coordination with the broader LangSmith platform. The ideal candidate has deep systems or database engineering experience and genuinely prefers to stay technical while growing a team. What you'll do - Write and review production Rust code across ingestion, query execution, and storage layers - Lead architectural decisions on storage format, compaction, indexing, and query planning - Drive performance investigations using memory and CPU profiling tools; own the path from profiling to shipped fix - Design and harden the distributed deployment of SmithDB services on Kubernetes (multi-tenant, high-throughput, low-latency) - Contribute to cloud object store integrations (S3, GCS, Azure Blob) and set the standard for how SmithDB manages data at rest and in flight - Build and maintain observability for the engine itself: metrics, tracing, debug tooling - Manage a small but growing team of systems engineers: set goals, run 1:1s, provide technical mentorship, and grow careers - Own the SmithDB technical roadmap in partnership with LangSmith product and engineering leadership - Communicate progress, risks, and tradeoffs clearly to the broader organization: you write concise, decision-ready updates What you'll bring - 7+ years in systems or database engineering, with at least 2 years in a technical lead or engineering management role - Production Rust experience — you can write it, review it, and have opinions on how to structure it at scale - Deep understanding of database or storage engine internals: query execution, storage layouts, indexing, compaction - Proficiency in systems performance analysis: memory allocators, CPU hotspots, lock contention, async runtimes (Tokio) - Experience deploying and operating distributed services on Kubernetes in a production, multi-tenant environment - Familiarity with cloud object storage (S3-compatible APIs, consistency models, cost/performance tradeoffs) - Proven track record of managing engineers — you can recruit, retain, and level-up a team without losing your technical edge Nice-to-have: - Experience building or contributing to columnar storage formats (Parquet, Arrow), OLAP query engines, or time-series stores - Background in observability infrastructure or tracing pipelines (OpenTelemetry, ClickHouse, Prometheus) - Experience scaling a system from early-stage to hundreds of billions / trillions of records Compensation Salary Range: $240,000-$300,000 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. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.