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LangChainLangChainNew York, NY

Deployed Engineer

This customer-facing technical role co-architects and deploys production AI agents, owns pre-sales evaluations, and advises customers after deployment. It requires 3+ years of relevant technical experience, strong Python and JavaScript skills, production LLM application experience, and willingness to travel 40%.

155k – 165k/yr
On-site3+ YOESales Engineering

About the role

Responsibilities

  • Co-architect and co-build production AI agents with customer engineering teams.
  • Own the technical win in pre-sales by designing proofs of concept, answering deep technical questions, and guiding evaluations.
  • Help customers deploy and operate agent-based applications, including conversational agents, research agents, and multi-step workflows.
  • Advise customers post-sale on architecture, best practices, and roadmap-level decisions.
  • Run technical demos, trainings, and workshops for developer audiences.
  • Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers.
  • Occasionally contribute code upstream when it meaningfully improves customer outcomes.
  • Travel 40% to customer sites for deployment, onboarding, and ongoing technical engagement.

Requirements

  • 3+ years in a relevant technical role, such as software engineering, customer engineering, solutions engineering, founding engineering, or product engineering.
  • Strong Python, JavaScript, and systems fundamentals.
  • Experience designing agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling.
  • Comfortable working directly with customers during proofs of concept, architecture reviews, and technical evaluations.
  • Able to explain technical tradeoffs clearly and build trust with developer audiences.
  • Ownership of outcomes, not just recommendations.
  • Bias toward action and comfort figuring things out as work evolves.
  • Interest in operating AI agents in production, not just building demos.

Nice to Have

  • Experience deploying AI agents in production, especially using LangChain, LangGraph, or similar frameworks.
  • Experience with LLM evaluation, observability, or guardrails.
  • Experience with cloud environments such as AWS, Google Cloud, or Azure; containers; and basic Kubernetes concepts.
  • Experience shipping and operating production software under real-world constraints.

Compensation

  • Annual OTE range: $155,000–$165,000+, depending on experience.
  • Compensation includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.

Benefits

  • Medical, dental, and vision coverage.
  • Flexible vacation.
  • 401(k) plan.
  • Meals on in-office days in the US.

Skills

PythonJavaScriptLangChainLangGraphllm evaluationllm observabilityguardrailsAWSGCPAzureContainersKubernetesAI AgentsSystem Designproofs of concept

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