---
title: 'Head of GTM Enablement at LangChain'
canonical: 'https://feeny.ai/job/head-of-gtm-enablement-langchain-san-francisco-m4dtpwev0gxh'
type: 'job'
last_seen: '2026-11-12'
---

# Head of GTM Enablement at LangChain

- **Company:** [LangChain](https://feeny.ai/companies/langchain)
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-11-06
- **Last confirmed live:** 2026-11-12
- **Apply:** https://jobs.ashbyhq.com/langchain/2f9100e9-655b-4244-9dab-9a37c153af6a

## 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 looking for a Head of GTM Enablement to build and scale the programs, systems, and habits that help our GTM teams perform. As product delivery accelerates and our portfolio and sales motions grow more complex, you’ll ensure the field keeps pace—turning new capabilities into effective execution without adding unnecessary overhead. You’ll lead a distributed enablement team and partner with leaders across Sales, Marketing, Product, Customer Engineering, Deployed Engineering, and Revenue Operations. You’ll balance global standards with role and regional needs so priorities translate across regions and roles. Success means faster ramp, stronger field execution, and measurable contributions to pipeline and revenue—not simply more training. You’ll own the strategy and orchestration behind AI in the field: one consistent, continuously current body of GTM knowledge that the tools other teams build can rely on, so delivery, effectiveness, measurement, and scaling all improve as the field grows. You’ll be equally deliberate about where humans remain essential: the conversations and strategic direction that enabling GTM at large requires.

## What You’ll Do

Set the global enablement strategy

- Define and execute a GTM enablement strategy aligned with revenue growth, customer expansion, and market priorities.
- Partner with executive and regional leaders to identify capability gaps and execution bottlenecks, directing investment toward the highest-impact opportunities.
- Own enablement planning, budget, governance, and operating cadence, with clear priorities, ownership, and success measures across onboarding, technical and product enablement, and outbound enablement.
- Decide where AI changes the enablement model and where human-led work stays, and set the standard the rest of GTM builds against.

Build programs that improve field performance

- Develop role-based enablement for Account Executives, Account Managers, Sales and Business Development Representatives, Partner/Channel Managers, Customer Engineering, and Deployed Engineering.
- Tailor programs by segment, industry, and geography where it improves execution, preparing teams to support multiple use cases, buyer types, and platform opportunities.
- Design and scale role-based 30/60/90-day onboarding that accelerates time to productivity and, for sellers, time to first deal.
- Establish continuous learning, coaching, and certification programs that reinforce skills beyond onboarding.
- Embed enterprise sales methodologies into day-to-day workflows, deal reviews, and pipeline inspections.
- Equip frontline managers to reinforce skills, inspect execution, and coach consistently—making enablement part of how teams operate, not a separate training activity.
- Structure programs so the knowledge behind them can be reused by AI-assisted practice, reinforcement, and certification, extending reach without proportional headcount.
- Keep human coaching where it changes behavior, so scalable programs extend reach without replacing the conversations that build skill.

Turn product knowledge into customer value

- Partner with Product Management and Product Marketing to deliver timely, role-specific training and certification as new capabilities launch.
- Own the internal training, practice, and reinforcement behind customer-facing messaging and assets, so GTM teams apply them effectively.
- Turn product and market expertise into practical playbooks, competitive guidance, demo guides, and value-selling resources that are current, easy to find, and useful in customer conversations.
- Own which assets are canonical, so every team and tool works from the same version as products and markets change.
- Turn patterns from customer conversations, deal outcomes, and field feedback into updates to that knowledge, so what the field and its tools know keeps improving.

Lead and scale a global team

- Build, coach, and develop a high-performing team of enablement professionals supporting team members across the Americas, EMEA and APAC.
- Establish clear decision rights and collaboration practices across global and regional teams, balancing consistency with local market needs and competitive dynamics.
- Hire and develop for knowledge architecture and program strategy, not just content production, so the function can run without depending on you.

Set the systems vision and own measurement

- Set the enablement technology vision across learning, content management, and conversation intelligence, and work with GTM Systems and GTM Engineering to execute it, including embedding enablement into workflows.
- Define what canonical GTM content exists, who maintains it, and how it stays current, so the tools GTM Systems and GTM Engineering build operate from one source instead of diverging copies.
- Lead the orchestration across GTM Systems, GTM Engineering, Product Marketing, and Revenue Operations, setting requirements for how their tools consume, refresh, and contribute back to that knowledge so quality compounds rather than drifts.
- Build measurement frameworks and executive reporting that connect enablement investments to skill application, behavior change, pipeline, and revenue outcomes across roles and regions.
- Use performance data, manager input, and field feedback to continuously improve programs and prioritize resources.

## What You’ll Bring

- 10+ years of relevant experience in GTM enablement within high-growth B2B SaaS organizations, including significant leadership experience.
- A demonstrated track record of building and scaling global enablement teams and programs across multiple regions.
- Experience supporting complex enterprise sales motions for technical products, enabling multiple GTM roles across use cases, buyer types, and the full buyer and customer lifecycle.
- Practical AI fluency, with the judgment to lead strategy and orchestration rather than build tools yourself: what AI can carry, what the knowledge behind it must look like, and where human judgment stays in the loop.
- Experience standing up or governing a shared knowledge or content system that multiple teams and tools depend on.
- Deep expertise in enterprise sales methodologies such as MEDDPICC, Command of the Message, Challenger, or Value Selling—and a practical approach to embedding them into field execution.
- Proven success designing onboarding, ongoing learning, product enablement, and manager coaching programs.
- Experience partnering with systems and engineering teams to deliver enablement technology, with enough fluency to set requirements without owning the platforms yourself.
- Strong analytical skills, with the ability to evaluate program effectiveness and communicate business impact to executive stakeholders.
- Exceptional communication, storytelling, and cross-functional influence skills.
- Credibility with field leaders and sellers, and the judgment to know when a conversation or coaching moment will move behavior more than a scalable program.
- A builder’s mindset: the ability to define strategy, systems, and standards while staying close to execution in a fast-moving environment.
- Bonus: experience leading or enabling customer-facing technical teams, such as Customer Engineering, Deployed Engineering, or Solutions Engineering, alongside a revenue organization.

## How We’ll Measure Success

- Shorter time to full productivity across GTM roles and faster time to first deal for sellers.
- Measurable contributions to improved win rates, average contract value, and pipeline velocity.
- Consistent application of core sales methodologies, reinforced through frontline manager coaching and deal execution.
- Demonstrated skill development and sustained behavior change—not just participation in training or adoption of tools.
- Field readiness that keeps pace with product delivery and growing business complexity, with teams prepared to execute on new capabilities, use cases, and sales motions as they launch.
- AI tools across GTM operating from one current knowledge base, with less rework, drift, and duplicated content, and less administrative work in delivery.
- Broader enablement coverage at a lower cost per program, showing the field reached more often without proportional headcount.
- Coaching quality as rated by managers and sellers, not just coaching activity.
- Improved field and manager satisfaction with enablement, alongside positive trends in GTM team retention.

Salary: $225,000-$255,000 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)

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