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职位LangChain

Senior Full Stack Engineer, Observability & Evals Platform

LangChain

Senior Full Stack Engineer, Observability & Evals Platform

LangChain

San Francisco, CA

·

On-site

·

Full-time

·

2mo ago

薪酬

$175,000 - $225,000

福利待遇

Equity

Learning

必备技能

Python

JavaScript

PostgreSQL

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 Senior Full Stack Engineer for our commercial product Lang Smith, an observability and evals platform. In this role, you'll have the opportunity to shape the technical direction of our platform while working closely with enterprise customers, developer end-users and internal stakeholders.

  • Lead the technical architecture and implementation of key product features for Lang Smith, working across our entire Go, Python, and Typescript stack.
  • Collaborate closely with product and design teams to iterate on new features.
  • Mentor and guide more junior members of the team. Drive aggressive project timelines while ensuring high engineering standards are being met.
  • Lead by example in writing clean, maintainable, and well-tested code

How to be successful in this role

  • 7+ 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.
  • Strong understanding of database systems, particularly Postgres and Redis
  • Experience designing and scaling APIs, preferably in a high-performance, data-intensive application
  • A “get stuff done” attitude - 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
  • Strong ownership mindset
  • 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: $175,000-$225,000 USD

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关于LangChain

LangChain

LangChain

Series B

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

51-200

员工数

San Francisco

总部位置

$200M

企业估值

评价

3.4

3条评价

工作生活平衡

2.5

薪酬

3.0

企业文化

2.8

职业发展

3.2

管理层

2.3

35%

推荐给朋友

优点

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

缺点

Uncertainty about long-term career prospects and employability

Projects rarely make it to production use

Lack of senior developer mentorship and guidance

薪资范围

13个数据点

Mid/L4

Senior/L5

Mid/L4 · Product Designer

1份报告

$178,619

年薪总额

基本工资

$155,147

股票

-

奖金

-

$178,619

$178,619

面试经验

10次面试

难度

2.7

/ 5

时长

14-28周

录用率

60%

体验

正面 50%

中性 40%

负面 10%

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Assessment/Take-home

4

Technical Interview

5

Virtual Onsite/Final Round

6

Offer

常见问题

System Design

Machine Learning/AI Knowledge

Coding/Algorithm

Technical Architecture

Behavioral/STAR