Deployed Engineer

🕒 il y a 1 jour

🌽 Illinois – Distant

🌽 Illinois – Remote

💵 $150 000 - $250 000 / an

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

👷🏻‍♀️ Ingénieur

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LangChain

Site WebLinkedInTous les Emplois

11 - 50 employés

🤖 Intelligence artificielle

🤝 B2B

☁️ SaaS

💰 €25 000 000 Series A en 2024-02

Artificial Intelligence • B2B • SaaS

LangChain est un cadre modulaire conçu pour aider les développeurs tout au long du cycle de vie des applications à base de grands modèles de langage (LLM). Leur suite de produits, comprenant LangGraph et LangSmith, offre des outils pour créer, déployer et gérer des applications capables de raisonner et d'opérer à grande échelle. Avec un accent sur l'efficacité opérationnelle et des performances améliorées, LangChain soutient un large éventail d'industries grâce à ses offres innovantes.

Description

• Co-architect and co-build production AI agents with customer engineering teams • Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations • Help customers deploy and operate agent-based applications such as 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 to customers up to 40% of the time

🎯 Exigences

• 6+ years in a relevant technical role, such as software engineering, customer engineering, solutions engineering, founding/product engineering • Experience ideally in a startup or scale-up • 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 POCs, architecture reviews, and technical evaluations • Ability to explain technical tradeoffs clearly and build trust with developer audiences • Responsibility for outcomes, not just recommendations • Bias toward action and ability to figure things out as you go • Excitement about operating AI agents in production • Nice to have: production AI agent deployment, especially using LangChain, LangGraph, or similar frameworks • Nice to have: experience with LLM evaluation, observability, or guardrails • Nice to have: experience with AWS, GCP, Azure, containers, and basic Kubernetes concepts • Nice to have: experience shipping and operating production software and owning systems under real-world constraints

🏖️ Avantages

• 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