(Senior) Frontend Engineer

Posted 6 Days Ago
Be an Early Applicant
Berlin
In-Office
Senior level
Artificial Intelligence • Software
Open Source LLM Engineering Platform
The Role
The Frontend Engineer will enhance the architecture for the frontend application, create dashboards for LLM execution insights, and develop performant table components and filtering interfaces.
Summary Generated by Built In
Frontend Engineer

In short: We're hiring a Frontend Engineer to build performant, scalable user interfaces for our rapidly growing LLM engineering platform.

About Langfuse
  • We are building the fastest growing open-source LLM engineering platform.

  • We help engineers and enterprises build and run LLM applications at scale.

  • We've raised $4m from Y Combinator, Lightspeed and General Catalyst.

  • Thousands of teams and engineers use Langfuse daily

  • Thousands are joining every month

  • We're a small, focused team working from Berlin, Germany.

What you'll do

Past projects you would have led:

  • Come up with an improved architecture for our frontend application

  • Build self-serve dashboards to generate insights into billions of LLM executions of our users

  • Creating performant table components with a focus on usability and fast rendering times

  • Implementing advanced filtering and search interfaces for complex datasets

Tech Stack

You should be familiar with a majority of these but we trust that you can pick up a new language/framework quickly.

  • React

  • Frontend and Backend in Typescript (including Express, NextJs, Tailwind, Prisma, tRPC)

What we're looking for
  • 3+ years of experience in frontend development

  • Experience building highly performant front-ends.

  • Strong understanding of React, TypeScript, and modern frontend tooling

  • Experience with state management and data fetching patterns

  • Hard worker and thrive working in a small and accountable team

  • Excited about open source software

  • A CS/quantitative degree is preferred

Bonus

  • Performance optimization and profiling experience

  • ML/AI experience

  • Impressive achievements from previous careers or side projects

  • Previous startup or founding experience

Why Langfuse?
  • You are joining really early

  • Strong Product Market Fit!

  • We are building a very small but highly capable team

  • Only hiring Engineering in foreseeable future

  • Strong customer & revenue growth

  • Building picks and shovels for the hottest AI companies

  • Building for very sophisticated technical users

  • Competitive salary & equity

  • Performance and learning focused culture

  • Everyone on the team says: "best place I've ever worked at"

How we work
  • Engineering based in Berlin ( we aim for 4-5 days in the office )

  • No more than 2 short scheduled meetings per week

  • Extreme ownership & autonomy how and what to work on

Hiring Process

We can run this process in less than 7 days.

  1. Fill out application

  2. We screen your application

  3. Jump on a intro call with our CTO

  4. Technical Deep Dive interview

  5. Super Day ( half or full day in Berlin Office )

  6. Meet the other founders (short calls)

  7. Decision & Offer

Links
  • Our codebase: GitHub Repository

  • Ben Kuhn on Impact, Agency and Taste

  • Who we are & how we work

Top Skills

Express
Nextjs
Prisma
React
Tailwind
Trpc
Typescript
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The Company
HQ: San Francisco, California
15 Employees
Year Founded: 2022

What We Do

Langfuse is the 𝗺𝗼𝘀𝘁 𝗽𝗼𝗽𝘂𝗹𝗮𝗿 𝗼𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲 𝗟𝗟𝗠𝗢𝗽𝘀 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺. It helps teams collaboratively develop, monitor, evaluate, and debug AI applications.

Langfuse can be 𝘀𝗲𝗹𝗳-𝗵𝗼𝘀𝘁𝗲𝗱 in minutes and is battle-tested and used in production by thousands of users from YC startups to large companies like Khan Academy or Twilio. Langfuse builds on a proven track record of reliability and performance.

Developers can trace any Large Language model or framework using our SDKs for Python and JS/TS, our open API or our native integrations (OpenAI, Langchain, Llama-Index, Vercel AI SDK). Beyond tracing, developers use 𝗟𝗮𝗻𝗴𝗳𝘂𝘀𝗲 𝗣𝗿𝗼𝗺𝗽𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁, 𝗶𝘁𝘀 𝗼𝗽𝗲𝗻 𝗔𝗣𝗜𝘀, 𝗮𝗻𝗱 𝘁𝗲𝘀𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 to improve the quality of their applications.

Product managers can 𝗮𝗻𝗮𝗹𝘆𝘇𝗲, 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗲, 𝗮𝗻𝗱 𝗱𝗲𝗯𝘂𝗴 𝗔𝗜 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀 by accessing detailed metrics on costs, latencies, and user feedback in the Langfuse Dashboard. They can bring 𝗵𝘂𝗺𝗮𝗻𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗹𝗼𝗼𝗽 by setting up annotation workflows for human labelers to score their application. Langfuse can also be used to 𝗺𝗼𝗻𝗶𝘁𝗼𝗿 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗿𝗶𝘀𝗸𝘀 through security framework and evaluation pipelines.

Langfuse enables 𝗻𝗼𝗻-𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝘁𝗲𝗮𝗺 𝗺𝗲𝗺𝗯𝗲𝗿𝘀 to iterate on prompts and model configurations directly within the Langfuse UI or use the Langfuse Playground for fast prompt testing.

Langfuse is 𝗼𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲 and we are proud to have a fantastic community on Github and Discord that provides help and feedback. Do get in touch with us!

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