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FullStack Engineer, Observability & Evals Platform (LangSmith)

LangChain

FullStack Engineer, Observability & Evals Platform (LangSmith)

LangChain

San Francisco, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$145,000 - $180,000

Benefits & Perks

Competitive salary and equity package

Comprehensive health, dental, and vision insurance

Professional development budget

Flexible work arrangements

Generous paid time off and holidays

Parental leave

Equity

Healthcare

Learning

Flexible Hours

Parental Leave

Required Skills

React

TypeScript

JavaScript

About Lang Chain

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: In person 5 days/week in San Francisco

We're looking for a Fullstack Engineer to work on Lang Smith, our commercial AI observability and evals platform product. In this role, you'll have the opportunity to build new features and functionality for the platform while working close enterprise customers, developer end-users and internal stakeholders.

What you will do:

  • Develop and implement key product features working across our entire Go, Python, and Typescript stack
  • Collaborate closely with product and design teams to iterate on new features and enhance the product roadmap
  • Drive aggressive project timelines while ensuring high engineering standards are being met by writing clean, maintainable, and well-tested code

How to be successful in this role

  • 2+ years of experience in software engineering working on complex platform products
  • Fullstack engineering experience with Go or Python on the backend and React + Typescript on the frontend
  • Solid understanding of database systems, particularly Postgres and Redis
  • Experience designing and scaling APIs, preferably in high-performance, data-intensive applications
  • Strong ownership and a “get stuff done” mindset - comfortable shipping fast and iterating based on user feedback
  • Strong communicator with the ability to collaborate closely with various internal stakeholders and engage directly with our top-tier customers
  • Bonus: Experience with AI/LLM-powered applications, developer tools, or observability platforms

Compensation & Benefits

  • 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: $145,000-180,000 USD

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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