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LangChain

Builds open-source tools for making AI agents

Deployed Architect - Professional Services

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeAustin, TX, USA

About the Job

Requirements

  • At least 7 years of experience in technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer.
  • At least 3 years of experience designing and deploying production infrastructure on cloud platforms such as Google Cloud Platform, Amazon Web Services, or Microsoft Azure.
  • Strong Kubernetes experience, including cluster design, autoscaling, and multi-zone deployments.
  • Experience with Infrastructure as Code using Terraform or Helm and GitOps practices.
  • Knowledge of database systems, including relational databases and in-memory data stores, with understanding of high availability, replication, backup strategies, and sizing.
  • Experience designing high-availability and disaster-recovery solutions.
  • Strong understanding of networking, security including single sign-on, role-based access control, Transport Layer Security, and secrets management, and observability tools such as Prometheus, Grafana, and Datadog.
  • Experience with continuous integration and continuous delivery pipelines for infrastructure and applications.
  • At least 1 year of experience building production artificial intelligence or machine-learning applications or agents.
  • Strong experience with large language model frameworks such as LangChain or LangGraph for building agent-based applications.
  • Experience with short-term and long-term memory state-management patterns.
  • Experience designing and implementing evaluation frameworks for artificial intelligence applications.
  • Strong prompt-engineering skills, including optimization and A/B testing.
  • Experience with vector stores, retrieval-augmented generation patterns, and knowledge organization.
  • Experience with tool integration, application programming interface design, and error-handling patterns.
  • Strong Python and/or TypeScript development skills.
  • Customer-facing experience with enterprise customers.
  • Experience conducting technical assessments or infrastructure audits.
  • Strong problem-solving skills to analyze complex requirements and design solutions.
  • Experience working cross-functionally with engineering teams, product teams, and customers.
  • A consultative approach to understanding customer needs, providing recommendations, and guiding implementation.
  • Ability to balance infrastructure architecture with agent development work.
  • Strong engineering background with hands-on development experience.
  • Willingness to travel up to 20% of the time.

Responsibilities

  • Design scalable, highly available infrastructure for artificial intelligence platform deployments, including compute, storage, networking, security, enterprise integration patterns, Infrastructure as Code, multi-region high-availability and disaster-recovery strategies, and continuous integration and delivery pipelines.
  • Design multi-agent systems using different patterns and implement agent logic using modern frameworks such as LangChain and LangGraph.
  • Design comprehensive evaluation frameworks and optimize prompts using A/B testing.
  • Guide agent deployment and operations.
  • Lead technical maturity assessments.
  • Work directly with enterprise customers to understand requirements and present recommendations.
  • Partner with Engagement Managers and Product and Engineering teams.

Desired Qualifications

  • The employer welcomes applicants with an unusual background, including former founders, if they have the necessary skill sets.

About the Company

LangChain

Builds open-source tools for making AI agents

LangChain makes free, open-source code libraries and a paid platform that software teams use to build and run AI agents, programs that use large language models to plan and finish tasks on their own. Its first library came out in October 2022, a month before ChatGPT, and in 2023 GitHub listed it among the open-source projects with the most contributors. Developers write agents with its LangChain, LangGraph, and Deep Agents libraries, which connect AI models to company data and software tools. Companies then pay for LangSmith, a platform that records each step an agent takes, scores its answers, and hosts finished agents. LangChain was founded in 2023 and is based in San Francisco.

Company size
201-500
Company stage
Series B
Total funding
$160M
Headquarters
San Francisco, CA
Founded
2023

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