---
title: 'Revenue Manager at LangChain'
canonical: 'https://feeny.ai/job/revenue-manager-langchain-san-francisco-t6ta7rtfzkks'
type: 'job'
last_seen: '2026-11-12'
---

# Revenue Manager at LangChain

- **Company:** [LangChain](https://feeny.ai/companies/langchain)
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-11-11
- **Last confirmed live:** 2026-11-12
- **Apply:** https://jobs.ashbyhq.com/langchain/2ec70ad4-e93f-4a51-a169-eef862fb3b64

## Job description

## About Us

At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.

## About the role

We're hiring our first Revenue Manager to own revenue accounting end to end: how we recognize it, how we close it, and the systems that produce it. You'll report to our Controller and work closely with rev ops, sales, legal, and FP&A. We sell through self-serve, enterprise contracts, and on marketplaces, with a mix of subscription, consumption, and self-hosted pricing as well as professional services. That mix makes revenue interesting. Prepaid credits, commits, overages, and multi-element deals all need clear policy and systems that get them right every month. This is a hands-on role. You'll write the accounting memos and also own how Salesforce, Metronome, and our ERP fit together so the numbers tie without a spreadsheet in the middle. We want someone who leans into AI. You'll use AI tools and agents to automate reconciliations, draft memos, and review contracts, and you'll help set how the rest of the accounting team works with them.

## What you'll do

Revenue recognition and policy

- Own ASC 606 for every way we sell: subscription, consumption, self-hosted licenses, and marketplace
- Write and maintain technical accounting memos and our revenue policy
- Build and maintain our standalone selling price (SSP) analysis and run allocations on multi-element deals
- Set the treatment for prepaid credits, commits, rollover, overages, breakage, and promotional credits
- Set revenue positions for new AI and consumption products, and track partner and marketplace economics as those models evolve
- Review deals before signature and advise sales and rev ops on how terms affect revenue

Close and reporting

- Run the monthly revenue close: usage revenue, deferred revenue, contract assets, and unbilled AR, with rollforwards and reconciliations
- Reconcile usage data, Metronome, Salesforce, and the GL every month
- Own the allowance for credit losses, from methodology through the audit memo, with collections and sales
- Produce revenue and deferred revenue flux analysis, RPO, and disaggregation, and present results in quarterly close reviews
- Partner with FP&A to tie ARR and usage metrics to GAAP revenue
- Own commission capitalization under ASC 340-40
- Support special projects like new pricing launches and products

Systems

- Own the revenue data flow from Salesforce to Metronome to our ERP and revenue subledger
- Design revenue rules and configuration in our AI-native ERP, and review its output rather than rebuild it in spreadsheets
- Lead requirements, testing, and parallel runs for new systems, products, and pricing launches
- Build automated reconciliations, controls, and AI agents so the close scales with the business

Audit and controls

- Own revenue for the annual audit: PBCs, memos, and walkthroughs
- Design revenue controls that would hold up to a SOX-level review

## What we're looking for

- 6 to 9 years of accounting experience, including 2+ years in public accounting (Big 4 or national firm) with technology clients
- 3+ years owning revenue accounting in-house at a high-growth software company, ideally with usage- or consumption-based pricing
- CPA preferred
- Deep, hands-on ASC 606 knowledge, including complex and non-standard arrangements: you've written the memos, built an SSP analysis, and defended your conclusions to auditors
- Business ownership of at least one revenue or billing system implementation, from requirements and data mapping through testing, parallel runs, and go-live
- A track record of replacing a manual process with an automated one
- Experience closing revenue under audit at a pre-IPO or public company
- You lean into AI. You already use AI tools or agents in your own work, can show where they made your close faster or more accurate, and want to build a revenue function that runs AI-first
- Clear writing and judgment. You can explain a revenue conclusion to a sales leader in two sentences and to an auditor in two pages

## Nice to have

- Experience with Metronome, Stripe Billing, or a similar usage-billing platform
- Experience with AI-native or modern ERPs, or NetSuite ARM, Zuora Revenue, or RightRev
- Accounting for self-hosted or on-prem software licenses alongside SaaS
- Cloud marketplace sales (AWS, GCP, Azure), including private offers
- IPO readiness or first-year SOX experience
- Experience at an AI, developer tools, or infrastructure company
- Built a revenue function or close process from scratch

Salary: $150,000-$180,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.

## Benefits

Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

## About LangChain

## Company Overview
- **One-liner**: LangChain provides an agent engineering platform and open source frameworks that help developers build, evaluate, deploy, and operate reliable AI agents at scale.
- **Entity Type**: Private (Series B, unicorn)
- **Headquarters**: San Francisco, California, United States (with offices in New York, Boston, and Amsterdam)
- **Founded**: Early 2023
- **Founders**: Harrison Chase and Ankush Gola

## Core Business
- **Primary industry/industries**: Artificial Intelligence, Developer Tools, Agent Engineering
- **Target customers**: B2B – developers and engineering teams at enterprises (35% of Fortune 500 are customers) and startups
- **Mission or purpose statement**: “Make intelligent agents ubiquitous” – develop tools that make it easy to build reliable agents that can use data and take actions.

## Products & Services
- **[LangSmith](https://www.langchain.com/)**: Commercial agent engineering platform offering observability, evaluation (LLM-as-judge, human feedback), and deployment. Includes LangSmith Engine for automated issue detection and root cause analysis. Supports Python, TypeScript, Go, and Java SDKs.
- **[LangGraph](https://www.langchain.com/)**: Open source framework for building production agents with low-level control, durable checkpointing, and support for human-in-the-loop, multi-agent swarms, and A2A/MCP protocols.
- **[LangChain](https://www.langchain.com/)**: Original open source framework for building agents quickly with templates and any model provider.
- **[Deep Agents](https://www.langchain.com/)**: Agent harness for autonomous, long-horizon tasks with built-in memory and concurrency.
- **[Fleet](https://www.langchain.com/)**: No-code agent builder that lets non-technical users describe tasks in plain language; agents act across daily tools with enterprise security.

## Market Standing
- **Valuation/Market Cap**: $1.25 billion (unicorn status, per November 2025 Series B round)
- **Key Metric**: Total Funding – $160 million (Seed: $10M led by Benchmark; Series A: $25M led by Sequoia Capital; Series B: $125M led by IVP). Annual Revenue (LinkedIn estimate): $8.5 million.
- **Notable Investors/Partners**: IVP (lead Series B), Benchmark (lead Seed), Sequoia Capital (lead Series A). Customers include Zip, Vanta, Klarna, Workday, LinkedIn, Cloudflare.
- **Growth Signals**:
  - Headcount: 212 employees (+264.8% YoY, +9.9% monthly)
  - 1 billion+ monthly open source downloads
  - 1 billion+ events ingested per day on LangSmith
  - 35% of Fortune 10 are LangSmith customers
  - 6,000+ active LangSmith customers
  - Awards: Forbes AI 50, InfraRed 100, IA40, Enterprise Tech 30
  - Active job postings: 123 (monthly +4.2%, yearly +668.8%)

## Competitive Advantages
- **Open source ecosystem**: LangChain and LangGraph are the most popular open source frameworks for building LLM agents, with a massive community (100M+ monthly downloads) that drives adoption and talent.
- **Full lifecycle platform**: Covers building (open source frameworks), evaluating (LangSmith), deploying (agent server), and operating (LangSmith Engine) – a vertically integrated solution.
- **Framework-agnostic**: LangSmith works with any agent stack (OpenAI, Anthropic, etc.) via SDKs, reducing vendor lock-in.
- **Enterprise trust**: Already embedded in Fortune 500 companies; strong security and compliance features for production AI.

## Strategic Focus
- **Agent reliability**: Investing heavily in evaluation and observability to make agents “reliably good” – the hardest problem in production AI.
- **Long-horizon autonomy**: Deep Agents and Fleet target autonomous, multi-step tasks that require memory and human collaboration.
- **Global expansion**: Offices in US, Europe, and India; hiring across sales, engineering, and customer success to serve a growing international customer base.

## Why Work Here
- **Culture**: Fast-moving, open source–first startup with a mission to shape how the world uses AI. Described as hiring “the best in the business” with a focus on engineering excellence.
- **Work policy**: Hybrid/office presence in San Francisco, New York, Boston, and Amsterdam. Remote roles may exist (not explicitly stated, but global hiring suggests flexibility).
- **Notable perks/engineering culture**:
  - Work on cutting-edge agent technology used by millions of developers.
  - High autonomy and impact – small team with big ambitions.
  - Strong alumni network from top tech companies (AWS, Datadog, HashiCorp, GitLab, etc.).
  - Recent departures include VP of Marketing (Diana Smith, Mar 2026) – indicates some churn, but overall rapid hiring.
  - Active job postings across engineering, sales, product, and consulting – strong growth trajectory.

## Sources
1. [langchain.com](https://www.langchain.com/) – Official website (products, stats, customers)
2. [langchain.com/careers](https://www.langchain.com/careers) – Careers page (awards, values)
3. [langchain.com/about](https://www.langchain.com/about) – About page (mission, history, funding, team)
4. [linkedin.com/company/langchain](https://www.linkedin.com/company/langchain) – LinkedIn profile (headcount, revenue, funding rounds, job trends, talent sources)

## Other roles at LangChain

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