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Marketing Operations Manager

LangChain

Marketing Operations Manager

LangChain

San Francisco, CA

·

On-site

·

Full-time

·

3d ago

ABOUT LANGCHAIN

At Lang Chain, 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, Lang Chain and Lang Graph, see over 90+ million downloads per month and help developers build agents with speed and granular control. Lang Smith offers observability, evaluation, and deployment for rapid iteration, enabling teams to transform LLM systems into dependable production experiences.

Lang Chain is trusted by millions of developers worldwide and powers AI teams at companies like Replit, Clay, Cloudflare, Harvey, Rippling, Vanta, Workday, and more.

ABOUT THE ROLE:

We’re looking for a Marketing Operations Manager to help scale the systems and data infrastructure behind our GTM engine.

This role owns supporting marketing in annual planning, managing the tech stack, attribution, data pipelines, reporting, automation, and campaign operations that enable the marketing and sales teams to operate effectively. You’ll work closely with Marketing, Sales, Rev Ops, and Data to ensure our GTM organization runs on clean data and reliable systems.

This is a highly cross-functional role ideal for someone who enjoys building systems, solving data problems, and turning complex funnels into actionable insights.

WHAT YOU WILL DO:

Strategy & Planning:

  • Partner with GTM leadership to define how marketing performance is measured across the funnel

  • Help develop the metrics framework for marketing impact, including pipeline generation, opportunity influence, and deal acceleration, etc.

  • Support annual planning and forecasting by providing data-driven insights into channel performance and pipeline contribution

  • Translate business questions from leadership into analytical frameworks and measurable KPIs

Campaign Operations

  • Support the execution of marketing programs across events, webinars, lifecycle, paid media, and field marketing

  • Manage campaign setup, tracking, and attribution across systems including Hub Spot, Salesforce, Bizzabo, Goldcast, Paid Ads, etc.

  • Ensure campaigns are properly structured to capture performance data across the full funnel

  • Maintain campaign taxonomy and naming conventions to ensure clean reporting

  • Partner with the marketing team to ensure campaigns are properly instrumented and measurable

Data, Analytics & Attribution

  • Build and maintain dashboards that measure marketing performance across the funnel

  • Develop and improve attribution models that measure how marketing influences pipeline and revenue

  • Analyze campaign performance, pipeline creation, and conversion metrics to identify opportunities for improvement

  • Partner with the data team to maintain marketing datasets and reporting infrastructure

  • Help leadership understand the drivers of pipeline growth through clear reporting and insights

Tooling & Automation:

  • Own the entire martech stack including Hub Spot, Salesforce, Segment, among others.

  • Maintain integrations between marketing, sales, and product data systems

  • Improve lead routing, lifecycle management, and data enrichment processes

  • Identify opportunities to automate manual workflows across marketing and sales operations

  • Evaluate and implement new tools that improve the efficiency of the GTM organization

How to be successful in this role:

  • 5+ years in Marketing Operations

  • Experience supporting annual planning, pipeline forecasting, and performance analysis to inform GTM strategy

  • Deep expertise with Hub Spot and Salesforce

  • Strong SQL skills and experience working with modern data stacks (Big Query, dbt, Reverse ETL, etc.)

  • Familiarity with web data and event tracking tools (Segment, Google Tag Manager, server-side tracking, etc.)

  • Proficiency using AI tools and LLM-powered workflows to improve productivity and automate GTM operations

  • Experience operating in a warehouse-first analytics environment, where the data warehouse serves as the source of truth for marketing and revenue reporting

  • Ability to build dashboards and reporting in BI tools (Looker, Tableau, Hex, etc.)

  • Experience with automation and integration platforms (Zapier, n8n, Workato, Make)

  • Experience owning and scaling a marketing technology stack, including vendor evaluation, system optimization, and identifying tool redundancies

  • Deep understanding of B2B SaaS funnels and gtm metrics

  • Ability to diagnose and improve complex marketing and GTM systems

  • Comfortable collaborating cross-functionally with marketing, sales, data, and engineering teams

Compensation & Benefits:

  • Compensation: We offer competitive compensation that includes base salary, meaningful equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation will vary based on role, level, and location. For team members in the EU and UK, we provide locally competitive benefits aligned with regional norms and regulations.

  • Annual salary range: $160,000- $240,000.00

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About LangChain

LangChain

LangChain

Series B

A platform that provides open-source frameworks and tools for engineering and deploying language model agents.

51-200

Employees

San Francisco

Headquarters

$200M

Valuation

Reviews

3.4

3 reviews

Work Life Balance

2.5

Compensation

3.0

Culture

2.8

Career

3.2

Management

2.3

35%

Recommend to a Friend

Pros

Working with cutting-edge AI technologies like LangChain and RAG

Hands-on experience building end-to-end AI projects

Exposure to modern applied AI development

Cons

Uncertainty about long-term career prospects and employability

Projects rarely make it to production use

Lack of senior developer mentorship and guidance

Salary Ranges

9 data points

Mid/L4

Mid/L4 · Product Designer

1 reports

$178,619

total / year

Base

$155,147

Stock

-

Bonus

-

$178,619

$178,619

Interview Experience

10 interviews

Difficulty

2.7

/ 5

Duration

14-28 weeks

Offer Rate

60%

Experience

Positive 50%

Neutral 40%

Negative 10%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Assessment/Take-home

4

Technical Interview

5

Virtual Onsite/Final Round

6

Offer

Common Questions

System Design

Machine Learning/AI Knowledge

Coding/Algorithm

Technical Architecture

Behavioral/STAR