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).

Workplace: Remote-friendly. European roles are remote-first with one week per month in Berlin. For US candidates, San Francisco is preferred, but we are open to exceptional candidates anywhere in the US.

TL;DR

We are hiring a Product Marketing Engineer who can understand Langfuse deeply, use the product hands-on, and explain it better than anyone else. In many companies, this would also be called a Developer Advocate.

This is a technical product advocacy role. You will write, build demos, improve docs, create launch content, speak at events, organize technical sessions, run product deep dives, explain how AI teams should think about observability/evals/prompt management, and help define how Langfuse shows up in the market.

The best person for this role is an engineer or highly technical product marketer who wants to educate through content. It is a strong plus if you already write publicly, have an audience, contribute to open source, or have original opinions that experienced AI engineers care about.

If you mainly want an events-and-community DevRel role, our Developer Relations Engineer (Events & Community) role is the better fit. This role is closer to the product: you should be technically strong enough to advocate for Langfuse with serious AI engineering teams, explain the details, and turn what you learn from the market back into better product communication.

Why Product Marketing Engineering at Langfuse

Langfuse needs technical product communication that is useful enough for strong engineers. The product sits inside real AI engineering workflows, so the best marketing looks like clear explanations, good demos, runnable examples, honest technical tradeoffs, useful docs, and opinionated launch material.

This role is for someone who wants to live close to the product and the market at the same time. You should be able to understand how a feature works, explain why it matters, build the example that proves it, and turn customer and community questions into better product communication.

What you'll do

Become a Langfuse subject matter expert across tracing, evals, prompt management, datasets, metrics, self-hosting, and the broader AI engineering workflow
Create product and technical marketing content: blog posts, product deep dives, guides, cookbooks, benchmarks, demos, webpages, docs, conference talks, social posts, launch videos, and more
Translate technical features and nuance into clear value propositions that help developers and teams understand why Langfuse matters
Work closely with product, engineering, and the ClickHouse product marketing team to launch new capabilities with sharp positioning and useful technical proof
Make our documentation, guides, and examples the best in the category
Build demo apps, code examples, and workshop material that users can actually run
Speak at, organize, and attend high-signal in-person events for AI engineers, including conferences, meetups, workshops, customer sessions, and ClickHouse field moments
Turn events into reusable product education: talks, demos, workshop repos, follow-up content, customer questions, sales learnings, and better positioning
Help define our content strategy and roadmap based on product priorities, customer questions, community signals, search demand, and what is happening in AI engineering right now
Conduct competitive and market analysis across LLM observability, evals, agent observability, prompt management, and related developer tooling
Use metrics and feedback to understand what is working, improve what is not, and recommend what we should do next
Spend time with users, community members, sales, solutions, and support so our product communication is grounded in real customer problems

What we're looking for

Must

You are an engineer, data scientist, developer advocate, product marketing engineer, or technical product marketer who can go deep on the product
You have 5+ years of relevant experience across engineering, technical product marketing, DevRel, data science, technical writing, developer tools, or a similar technical field. Exact title matters less than work quality
You can write exceptionally well. You make complex technical ideas feel simple without making them shallow
You can code enough to build examples, inspect SDKs, understand traces, and be credible with strong engineers
You can advocate for a technical product in person and in writing. You are comfortable explaining why something matters, not just how it works
You have taste in good content and strong opinions about what makes technical writing useful
You can own projects end to end, from messy input to shipped public asset
You can collaborate well across product, engineering, marketing, sales, solutions, support, and ClickHouse counterparts
You are curious about AI engineering and stay close to what developers are actually building

Extras

You already create content: blog posts, videos, talks, social posts, newsletters, docs, open-source examples, or technical explainers
You already have an audience, or clear evidence that experienced technical people value your explanations
You have worked in engineering, product marketing engineering, DevRel, data infrastructure, observability, databases, AI tooling, or developer tools
You are deep in LLM applications, agents, evals, prompt engineering, RAG, or observability
You have run benchmarks, written competitive deep dives, or produced opinionated technical market analysis
You have spoken at technical events, organized developer events, run workshops, or built community around a technical product
You contribute to open-source projects
You are comfortable on camera and on stage
You know ClickHouse, SQL, analytics systems, or data infrastructure

Our Process

We can run this process quickly when calendars line up.

Fill out application
We screen your application
Screening Call: Quick intro and logistics, remote
Founder Call: Founder / Product Marketing deep dive, 40 min, remote
Deep Dive: Technical product explanation, writing, and demo deep dive, 60 min, remote
Super Day: half or full day with the team, in office when possible, remote in some cases
Meet the other founders, short calls
Decision and offer

Some technical product marketing work we like

Vercel: developer-first product marketing, launch quality, and high-trust content
Sentry: developer-first marketing for observability, performance, product launches, and digital conversion
ClickHouse: technical product marketing, benchmarks, practitioner-led content, and infrastructure category building
Swyx / Latent Space: original market framing, technical taste, and public point of view
Simon Willison: technical writing with a clear point of view

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.