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Customer Engineer

LangChain

Customer Engineer

LangChain

United States

·

On-site

·

Full-time

·

2w ago

Compensation

$145,000 - $175,000

Benefits & Perks

Healthcare

401(k)

Equity

Flexible Hours

Life Insurance

Healthcare

401k

Equity

Flexible Hours

Required Skills

Python

Technical training

Customer enablement

AI/ML

Communication

ABOUT US

At Lang Chain, 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.

Today, Lang Chain, Lang Graph, Lang Smith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust Lang Chain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.

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. Lang Chain is a place where your contributions can shape how this technology shows up in the real world.

ABOUT THE ROLE:

We're looking for a Customer Engineer to join our Enterprise Enablement team. In this role, you will serve as a trusted technical advisor to our new customers, blending technical expertise with a passion for education and enablement. You will be instrumental in accelerating developer and enterprise success with the Lang Chain ecosystem.

You'll join a collaborative team environment with a strong engineering culture, with direct impact on customer success and the opportunity to shape best practices while working with cutting-edge AI technology.

WHAT YOU'LL DO:

  • Lead onboarding engagements for new enterprise customers, guiding them through initial setup and unblocking issues as they begin building on the Lang Smith platform

  • Create and deliver live, interactive training workshops to help customer teams build foundational product knowledge and agent engineering best practices

  • Develop scalable enablement frameworks including technical tutorials, best-practice guides, and reference implementations

  • Act as the voice of the new user, synthesizing feedback and identifying friction points to inform the product roadmap in collaboration with Product and Engineering teams

  • Partner with Sales, Deployed Engineering, and Professional Services to define enablement strategies for prospective customers, demonstrating the value and ease of getting started with Lang Chain

  • Stay at the forefront of agent engineering in industry to identify evolving trends and quickly incorporate learnings into customer enablement materials

WHAT WE'RE LOOKING FOR:

  • 5+ years of experience in a technical, customer-facing role such as Enablement, Customer Success Engineer, Developer Advocate, or similar

  • Proven software engineering experience with 2+ years focused on AI/ML applications or agents, including strong proficiency in Python and a deep, practical understanding of the modern AI/LLM stack

  • Passion for educating users on technical topics and deep empathy for the developer experience

  • Demonstrated ability to create and deliver high-quality technical training programs, including live workshops, written tutorials, documentation, and video guides

  • Exceptional presentation and communication skills, with the ability to explain complex technical concepts to diverse audiences, from individual developers to enterprise stakeholders

  • Capacity to operate independently in a fast-paced, ambiguous environment and manage multiple projects simultaneously

  • Ability and willingness to travel up to 20% of time for customer engagements

Preferred:

  • Hands-on experience building and deploying applications using Lang Chain, Lang Graph, and Lang Smith (or similar frameworks)

  • Proficiency with TypeScript/Java

Script in addition to Python:

Location: San Francisco or New York preferred. Open to remote candidates within the US.

Compensation:

  • We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.

  • Competitive salary based on location and experience: $145K - $175K

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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