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LangChain Tech Stack

Agent engineering platform with observability and deployment tools

Technology, Information and Internet San Francisco, CA 51–200 employees Privately Held
langchain.com LinkedIn

LangChain operates an open-source-first platform for building and deploying AI agents, centered on three components: LangChain and LangGraph frameworks, the LangSmith observability/evaluation suite, and emerging Deep Agents tooling. The stack reveals a production-oriented company — Kubernetes, PostgreSQL, Redis, ClickHouse, and Datadog across GCP/AWS/Azure — paired with aggressive hiring (98 roles in 30 days, heavily weighted to senior engineers) and a project list focused on production reliability: multi-tenant performance testing, agent observability at scale, and internal diagnostics for production triage.

Tech Stack 40 technologies

Core StackPython TypeScript Go AWS Kubernetes JavaScript Terraform Helm React Vite Webpack PostgreSQL Redis ClickHouse Playwright Docker Datadog OpenTelemetry GCP SLSA sigstore cosign LangSmith LangGraph Azure Babel npm k6 Fleet AWS EKS+7 more
AdoptingSAML OIDC SCIM LangSmith LangGraph Fleet

What LangChain Is Building

◆Challenges

  • Operating agent-based applications at scale
  • Pre-sales technical win
  • Operating agents reliably at scale
  • Debugging production issues
  • Deploying agent-based applications
  • Scaling prototypes to production
  • High-volume observability data
  • Ensuring reliability and scalability
  • Scaling enterprise adoption
  • Customer churn risk

▲Active Projects

  • Co-architect production ai agents
  • Langsmith observability and evals platform
  • Go-to-market motion
  • Design pocs for pre-sales
  • Deploy and operate agent-based applications
  • Internal tooling and diagnostics for issue triage
  • Open canvas reference agent
  • K6 performance scenario for multi-tenant traffic
  • Ephemeral end-to-end testing harness for langsmith stack
  • Create reusable patterns and cookbooks

Hiring Activity

Accelerating100 roles · 100 in 30d

Department

Engineering
60
Sales
15
Support
11
HR
5
Marketing
2
Product
2
Security
2
Finance
1

Seniority

Senior
70
Mid
14
Director
5
Manager
5
Junior
3
Principal
1
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About LangChain

LangChain builds the platform for agent engineering at scale. The product spans three layers: open-source frameworks (LangChain, LangGraph, Deep Agents) for developers to architect agents; LangSmith, a proprietary observability, evaluation, and deployment layer for teams iterating on production systems; and internal tooling for diagnostics and issue triage. The company sells to AI teams at mid-market and enterprise buyers. With 51–200 employees headquartered in San Francisco and hiring across six countries (US, Singapore, UK, Canada, Netherlands, Australia), LangChain operates a hybrid open-source and commercial model, with the open frameworks driving developer adoption and LangSmith serving as the conversion point for teams moving agents into production.

HeadquartersSan Francisco, CA
Company Size51–200 employees
Hiring MarketsUnited States, Singapore, United Kingdom, Canada, Netherlands, Australia

Frequently Asked Questions

What is LangChain's tech stack?

LangChain uses Python, TypeScript, Go, Kubernetes, PostgreSQL, Redis, ClickHouse, and GCP/AWS/Azure. Observability runs on Datadog and OpenTelemetry. They're adopting SAML, OIDC, SCIM for identity, plus their own LangSmith and LangGraph products.

What is LangChain working on?

Core projects include LangSmith observability and evaluation platform, production AI agent architecture, agent deployment and operation tooling, multi-tenant performance testing (k6), and internal diagnostics for production issue triage. Go-to-market and pre-sales POC design are also active.

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How this profile is built

LangChain's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.