Senior Backend Engineer, LangSmith Deployments

Reposted 2 Days Ago
Be an Early Applicant
2 Locations
In-Office
175K-225K Annually
Senior level
Information Technology • Software • Database
The Role
Build and operate the LangSmith Deployments runtime for long-running AI agents: design distributed queue/worker systems, own state persistence and job claiming, implement resumable streaming, instrument production systems, participate in on-call and incident response, produce system documentation, and contribute to open-source LangGraph.
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, LangChain, LangGraph, LangSmith, and Fleet are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.

About the Team

The Deployment team builds the platform that runs AI agents in production. We design and scale the core durable execution runtime to power reliable long-running agents with resumable streaming and inter-agent protocol support. We work closely with open source and other product teams to make it easy to bring any agent from prototype to production.

About the role

We're building purpose-built infrastructure for running AI agents. Unlike traditional web apps, agents run for long durations, collaborate asynchronously with humans and other agents, and need to survive failures mid-execution. LangSmith Deployments is the runtime that makes this work, with durable checkpointing, fault-tolerant orchestration, and horizontal scaling, deployed across cloud and self-hosted environments.

What You'll Do

We're looking for a Senior Backend Engineer to work on this system. While the focus is on backend development, strong familiarity with Kubernetes (K8s), Terraform (Tf), and other DevOps tooling is highly preferred.

  • Design distributed queue and worker systems that handle concurrent agent execution, background tasks, and multi-agent coordination across horizontally scalable infrastructure

  • Own core data infrastructure — state persistence, atomic job claiming, connection management, and schema evolution

  • Collaborate on architectural decisions, ensuring solutions are scalable and robust.

  • Ship resumable streaming infrastructure so clients can disconnect and reconnect mid-execution without losing state

  • Instrument and monitor production systems — tracing, metrics, and alerting to keep the platform healthy

  • Participate in on-call rotations and own incident response for the runtime

  • Create and maintain technical documentation, including system design and operational runbooks.

  • Contribute to and extend open-source LangGraph, which is used by thousands of developers to build agent applications

What You'll Bring
  • 4+ years of professional backend engineering experience

  • Strong proficiency in Go and/or python

  • Experience with distributed systems — conensus mechanisms, queueing, state machines, and/or workflow orchestration

  • Experience with scaling and sharding databases in high throughput environments

  • Familiarity with Kubernetes, infrastructure-as-code, and at least one major cloud platform

  • Strong communication skills and ability to work cross-functionally on a small team

  • Annual salary range: $175,000-$240,00 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

  • 4+ years of professional backend engineering experience
  • Strong proficiency in Go and/or Python
  • Experience with distributed systems (consensus, queueing, state machines, workflow orchestration)
  • Experience with scaling and sharding databases in high-throughput environments
  • Familiarity with at least one major cloud platform
  • In person 5 days/week in San Francisco, CA or New York, NY
  • Participation in on-call rotations and incident response
  • Strong communication skills and ability to work cross-functionally
  • Strong familiarity with Kubernetes and Terraform (DevOps tooling)
  • Experience contributing to or extending open-source projects (e.g., LangGraph)
Am I A Good Fit?
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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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