Senior Frontend Engineer

Posted 2 Days Ago
Be an Early Applicant
5 Locations
Hybrid
Senior level
Artificial Intelligence • Software
Open Source LLM Engineering Platform
The Role
Build and optimize performant React UIs for large LLM traces, own frontend architecture and components, collaborate with designers, ship end-to-end features, and connect/extend tRPC APIs.
Summary Generated by Built In
About Langfuse

Open Source LLM Engineering Platform that helps teams build useful AI applications via tracing, evaluation, and prompt management (mission, product). We are now part of ClickHouse.

We're building the "Datadog" of this category; model capabilities continue to improve, but building useful applications is really hard, both in startups and enterprises.

Largest open source solution in this category: trusted by 19 of the Fortune 50, >2k customers, >26M monthly SDK downloads, >6M Docker pulls.

We joined ClickHouse in January 2026 because LLM observability is fundamentally a data problem and Langfuse already ran on ClickHouse. Together we can move faster on product while staying true to open source and self-hosting, and join forces on GTM and sales to accelerate revenue.

Previously backed by Y Combinator, Lightspeed, and General Catalyst.

We're a small, engineering-heavy, and experienced team in Berlin and San Francisco. We are also hiring for engineering in EU timezones and expect one week per month in our Berlin office (how we work).

In Short: We're looking for a senior frontend engineer to build the UI for the most widely adopted open source LLM engineering platform — where the core challenge is rendering massive, data-intensive views fast and making complex workflows feel simple.

Why Frontend Engineering at Langfuse

Your work will have an outsized impact.

Thousands of users sign into Langfuse daily to inspect traces, update prompts, and run experiments. They obsess over what they see in Langfuse to improve the systems they just shipped to production. Megabytes of JSON data should be available at their fingertips, searchable and presented in a readable way. Your job is to make that experience fast and intuitive.

When you ship an improvement to a view, eager users often find your PR and give feedback before you've even released it. They'll tweet about it before you write a changelog post. Everything you build is open source (MIT-licensed) and immediately visible.

You will also have direct exposure to how cutting-edge LLM applications are built. The users you serve are some of the best and most ambitious software engineers in the world, and they leverage Langfuse to understand and improve their applications. Deeply understanding their workflows will help you design the best possible UI — and along the way makes you an expert on LLM engineering yourself.

What you'll do
  • Build performant rendering for large LLM data — Langfuse displays full LLM inputs and outputs, which can be tens of thousands of tokens per observation. You'll own the performance of our trace views, finding bottlenecks in rendering, data loading, and reducing rerenders so that even the largest agent traces feel local-level snappy. You love diving deep into profiling re-renders? This is a match!

  • Own our React setup - you can shape and own how we build components, structure our code and write tests. Make our React setup thrive for agents and be up-to-date with new features (for example the React Compiler).

  • Build complex interactive features — recent examples: agent graph visualization that infers execution flow from observation timings, a redesigned trace view with tree/timeline toggle and search, inline comments anchored to specific text selections (like Google Docs), and dashboard widgets for tool usage analytics. These are the kinds of features you'll own end-to-end.

  • Own UI/UX across the product — you'll work closely with a designer to improve the experience across all of Langfuse. This means thinking about visual consistency and begin to build out a design system. You'll think deeply about how to present complex data in our product.

  • Ship features end-to-end — while your focus is the frontend, you'll connect to our tRPC APIs and sometimes extend them. We don't have hard boundaries — if a feature needs a backend change, you'll make it.

What we're looking for
  • Senior frontend engineer who cares deeply about performance — you love to profile React renders, debugged layout thrashing, and know when to virtualize, memoize, or restructure

  • Strong in React, TypeScript, and modern CSS — you write clean, maintainable component code

  • Like to collaborate with a designer to turn complex requirements into intuitive interfaces

  • Someone who can PM and project-manage themselves — you have strong opinions about what to build and how to ship it. Talking to users makes you happy.

  • Interest in open source software and genuine enjoyment talking to users about their experience

  • Thrives in a small, accountable team where your output is visible and matters

  • CS or quantitative degree preferred

Bonus points:

  • Experience with large data applications and rendering this on the frontend

  • Former founder

  • Background in data visualization or building developer tools

Links
  • Feature you could have built: Agent Graph Visualization

  • Feature you could have built: Redesigned Trace View

  • Feature you could have built: Inline Comments on Observations

  • Our codebase: GitHub Repository

  • React Performance Tracks

  • You link to this article often

  • Ben Kuhn on Impact, Agency and Taste

  • Who we are & how we work

Process

We can run the full process to your offer letter in less than 7 days (hiring process).

Tech Stack

We run a TypeScript monorepo: Next.js on the frontend, Express workers for background jobs, PostgreSQL for transactional data, ClickHouse for tracing at scale, S3 for file storage, and Redis for queues and caching. You should be familiar with a good chunk of this, but we trust you'll pick up the rest quickly (Stack, Architecture).

How we ship

Link to handbook

  • We trust you to take ownership (ownership overview) for your area. You identify what to build, propose solutions (RFCs), and ship them. Everyone here thinks about the user experience and the technical implementation at the same time. Everyone manages their own Linear.

  • You're never alone. Anyone from the team is happy to go into a whiteboard session with you. 15 minutes of shared discussion can very much improve the overall output.

  • We implement maker schedule and communication. There are two recurring meetings a week: Monday check-in on priorities (15 min) and a demo session on Fridays (60 min).

  • Code reviews are mentorship. New joiners get all PRs reviewed to learn the codebase, patterns, and how the systems work (onboarding guide).

  • We use AI as much as possible in our workflows to make our users happy. We encourage everyone to experiment with new tooling and AI workflows.

Why Langfuse (now part of ClickHouse)
  • This role puts you at the forefront of the AI revolution, partnering with engineering teams who are building the technology that will define the next decade(s).

  • This is an open-source devtools company. We ship daily, talk to customers constantly, and fight for great DX. Reliability and performance are central requirements.

  • Your work ships under your name. You'll appear on changelog posts for the features you build, and during launch weeks, you'll produce videos to announce what you've shipped to the community. You’ll own the full delivery end to end.

  • We're solving hard engineering problems: figuring out which features actually help users improve AI product performance, building SDKs developers love, visualizing data-rich traces, rendering massive LLM prompts and completions efficiently in the UI, and processing terabytes of data per day through our ingestion pipeline.

  • You'll work closely with the ClickHouse team and learn how they build a world-class infrastructure company. We're in a period of strong growth: Langfuse is growing organically and accelerating through ClickHouse's GTM. (Why we joined ClickHouse)

  • If you wonder what to build next, our users are a Slack message or a Github discussions post away.

  • You’re on a continuous learning journey. The AI space develops at breakneck speed and our customers are at the forefront. We need to be ready to meet them where they are and deliver the tools they need just-in-time.

Top Skills

React,Typescript,Next.Js,Trpc,Express,Node.Js,Postgresql,Clickhouse,Aws S3,Redis,Modern Css,React Compiler,Github,Linear
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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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