At LangChain, our mission is to make intelligent agents ubiquitous. We provide the agent engineering platform and open source frameworks developers need to ship reliable agents fast.
Our open source frameworks, LangChain and LangGraph, see over 90+ million downloads per month and help developers build agents with speed and granular control. LangSmith offers observability, evaluation, and deployment for rapid iteration, enabling teams to transform LLM systems into dependable production experiences.
LangChain is trusted by millions of developers worldwide and powers AI teams at companies like Replit, Clay, Cloudflare, Harvey, Rippling, Vanta, Workday, and more.
Location: San Francisco, CA (onsite)
We're looking for a Growth Marketer to own the journey from LangSmith signup to paying self-service customers. In this role, you'll be responsible for driving self-service activation and monetization through experimentation across email, lifecycle marketing, onboarding programs, and community-driven growth initiatives.
This is a high-impact role where you'll work cross-functionally with growth engineering, customer engineering, education, and community to accelerate adoption of LangSmith. If you're a builder who loves testing hypotheses, analyzing data, and moving fast in unstructured environments, we'd love to hear from you. Today, we have a significant opportunity to optimize the path from free to paid—you'll get to shape this conversion engine from the ground up.
This is a roll up your sleeves role.. You'll write email sequences, build webinar content, analyze cohort data, and run experiments yourself. If you are passionate about using AI to get results, this could be a great fit.
Own signup-to-paid conversion: Drive the strategy and execution to convert free LangSmith users into paying customers, owning the conversion rate and revenue impact
Build lifecycle marketing programs: Create and optimize email campaigns, in-product messaging, and nurture sequences that guide users through activation, engagement, and conversion
Run experiments: Test new initiatives like onboarding webinars, product demos, educational content series, and other conversion-focused programs to identify what moves the needle
Partner with growth engineering: Collaborate closely with engineering and product to implement product changes and in-product experiments that improve conversion rates
Drive the startup program: Work to scale our startup program, turning it into a meaningful pipeline of engaged, converting users
Analyze and iterate: Dive deep into user data, cohort analysis, and conversion funnels to identify drop-off points and opportunities for improvement
Write compelling copy: Craft emails, landing pages, webinar scripts, and messaging that resonates with developers and technical decision-makers, partnering with product marketing
Build scalable systems: Implement processes, automation, and frameworks that enable repeatable, data-driven growth as we scale
Experience: 4-6 years in growth, growth marketing, business operations, consulting, venture capital, or investment banking
Proven impact: Track record of driving measurable business results through experimentation, analysis, and execution
Strong writing: Excellent writing skills with the ability to craft clear, compelling copy for technical audiences including emails, landing pages, and other content
Analytical mindset: Comfortable with data analysis - you use data to drive decisions making and can identify patterns in user behavior to inform strategy
Builder mentality: You are scrappy and hands-on, willing to do what it takes to test a hypothesis and learn quickly
Technical acumen: Ability to understand and communicate technical concepts - bonus if you're familiar with LangChain, LangSmith, and/or AI/ML concepts
Cross-functional collaboration: Strong communication skills and experience working effectively with engineering, customer engineering, and community teams to drive shared goals
Ownership mentality: You're a self-starter who thrives in ambiguity, takes initiative, and drives results
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LangChain’s flexible abstractions and extensive toolkit unlocks developers to build context-aware, reasoning LLM applications.
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