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).
Why this role existsLangfuse has grown mostly through product-led, open-source adoption. We built a strong product, wrote useful docs and examples, stayed close to users, shipped in public, and helped developers understand how to build better AI applications.
Since being acquired by ClickHouse, with access to ClickHouse's broader GTM resources, Langfuse now has a growing enterprise motion and a large self-hosted user base.
This role exists to give Langfuse a clear, accurate narrative that is easier to understand and adopt.
How The Role WorksThis role is for a product marketer who likes technical depth. A technical background is a strong plus, but if you don't have one, curiosity and a drive to go deep will take you just as far.
You'll become a true power user of Langfuse, and gain a front-row seat into how the best AI teams build production applications.
You should expect close working relationships with both Langfuse teams and ClickHouse’s product marketing, sales and regional GTM teams.
What we're looking forSubstantial experience in product marketing, product, or a technical role, including time spent on industry or vertical marketing.
Past track record of crafting compelling messaging, positioning, and value propositions that resonate with developers, technical buyers, AI teams, enterprise stakeholders, and other highly technical audiences.
Excellent written and verbal communication skills, with the ability to articulate complex
concepts clearly and concisely.
Analytical mindset with the capacity to leverage data and metrics to measure performance in open-source PLG funnels and inform decision-making.
Cross-functional collaborator comfortable working with stakeholders across functions and levels.
A strong plus if you have a background in dev tools, open source, observability, or data/cloud infra; and/or if you have an existing public content or writing presence.
Build messaging, positioning, and value props that work for developers, technical buyers, and enterprise stakeholders alike
Own the category narrative (LLM observability, evals, prompt management, agent observability, self-hosting)
Create sales enablement and marketing collateral and assets, including website content, blogs, webinars and presentations, launch narratives, and more
Conduct competitive analysis to understand market trends, identify opportunities, and inform product and marketing strategies
Evaluate and iterate on strategies with metrics and feedback from stakeholders to track efficacy, identify areas for improvement, and make data-driven recommendations
Lead product and feature launches, and spend time with users, customers, prospects, sales, support, and community members.
We can run the full process to your offer letter in less than 7 days (hiring process).
Tech StackWe 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 shipLink 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.
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.
Skills Required
- Substantial experience in product marketing, product, or a technical role, including industry or vertical marketing
- Proven track record creating messaging, positioning, and value propositions for developers, technical buyers, AI teams, and enterprise stakeholders
- Excellent written and verbal communication skills, able to articulate complex concepts clearly
- Analytical mindset; able to use data and metrics to measure open-source PLG funnels and inform decisions
- Cross-functional collaboration experience working with product, sales, support, and community stakeholders
- Willingness to spend approximately one week per month in the Berlin office (hybrid expectation)
- Background in dev tools, open source, observability, or data/cloud infrastructure
- Familiarity with the tech stack (TypeScript, Next.js, Express, PostgreSQL, ClickHouse, S3, Redis)
- Public content or writing presence (blogs, talks) is a strong plus
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!







