Infrastructure Engineer, Database

Posted Yesterday
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San Francisco, CA, USA
In-Office
180K-230K Annually
Senior level
Information Technology • Software • Database
The Role
Own the infrastructure, deployment, and operational reliability of SmithDB, a distributed database for AI observability. Responsibilities include Kubernetes and cloud cluster management, infrastructure as code, CI/CD, upgrades, failover, incident response, SLOs, disaster recovery, capacity planning, cost optimization, and production rollouts across AWS, GCP, and Azure. The role partners with database engineers to safely deploy engine improvements at large scale.
Summary Generated by Built In
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.

Skills Required

  • 5+ years of experience in infrastructure, platform engineering, or SRE
  • Hands-on experience with Kubernetes and cloud infrastructure, including AWS, GCP, or Azure
  • Scripting or systems programming ability with Go, Python, or a similar language
  • Experience with infrastructure-as-code and CI/CD tooling such as Terraform, Helm, or ArgoCD
  • Deep familiarity with at least one major cloud provider and stateful workload infrastructure primitives
  • Infrastructure-as-code fluency using Terraform, Pulumi, CDK, or similar tools
  • On-call experience supporting high-traffic data systems and strong incident response skills
  • Experience deploying and operating stateful workloads in production using Kubernetes
  • Strong written and oral communication skills
  • Production ownership of database systems such as Postgres, ClickHouse, or Redis
  • Ability to read and reason about Rust
  • Understanding of database reliability concepts including replication, backups, point-in-time recovery, connection pooling, and graceful degradation
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The Company
123 Employees

What We Do

LangChain is the platform for building reliable agents. Our products power top engineering teams — from fast-growing startups like Lovable, Mercor, and Clay to global brands including AT&T, Home Depot, and Klarna. LangGraph is a low-level orchestration framework for building controllable agents and long-running workflows. It’s used in production by teams at Replit, Uber, LinkedIn, GitLab, and more. LangSmith offers unified evaluation and monitoring to help developers debug, evaluate, and improve their agents at scale. LangChain provides hundreds of integrations and composable components, making it easy to connect with the latest models, tools, and databases — with minimal engineering overhead. Together, these tools help teams build, deploy, and manage enterprise-grade agents, faster.

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