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Solutions Engineer

🕒 August 13

🤠 Texas – Remote

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⏰ Full Time

🟡 Mid-level

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 31%

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Logo of LangChain

LangChain

11 - 50 employees

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

💰 $25M Series A on 2024-02

Artificial Intelligence • B2B • SaaS

LangChain is a composable framework designed to assist developers throughout the entire lifecycle of Large Language Model (LLM) applications. Their suite of products, including LangGraph and LangSmith, offers tools for building, deploying, and managing applications that can reason and operate at scale. With a focus on operational efficiency and improved performance, LangChain supports a wide range of industries through its innovative offerings.

📋 Description

• Partner with account executives to scope evaluations, conduct technical discovery, and design customer-specific proofs of concept • Serve as the technical authority during architecture reviews, security and infrastructure discussions, and competitive evaluations • Co-architect and co-build production AI agents with customer engineering teams from prototype through rollout • Help customers deploy and operate conversational agents, research agents, and multi-step workflows • Run demos, trainings, and workshops for developer audiences • Advise customers post-sale on architecture, best practices, and roadmap-level decisions • Identify expansion opportunities from post-sale customer conversations • Surface field feedback to product teams • Build reusable POC assets, cookbooks, and example code • Contribute code upstream when it improves customer outcomes

🎯 Requirements

• 6+ years in a relevant technical role such as solutions engineering, sales engineering, customer engineering, software engineering, or founding and product engineering • Experience ideally at a startup or scale-up • Ability to own the technical thread through discovery, proofs of concept, architecture reviews, and competitive evaluations • Ability to explain technical tradeoffs clearly and build trust with developer audiences • Track record of taking responsibility for outcomes, not just recommendations • Bias toward action and willingness to figure things out as needed • Genuine interest in operating AI agents in production • Experience deploying AI agents in production, especially with LangChain, LangGraph, or similar frameworks (nice to have) • Experience carrying a technical number or working against pipeline alongside a sales team (nice to have) • Experience with LLM evaluation, observability, or guardrails (nice to have) • Experience with AWS, GCP, or Azure, containers, and basic Kubernetes concepts (nice to have)

🏖️ Benefits

• Medical coverage • Dental coverage • Vision coverage • Flexible vacation • 401(k) plan • Meals on in-office days in the US • Variable compensation for relevant roles • Meaningful equity • Competitive benefits and perks

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