(Senior) Backend Engineer

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 are hiring a (senior) Backend Engineer to make our systems and infra keep up with our globally growing user base and billions of monthly events to process.

Past projects you would have led:

• Optimizing the latency of complex database queries in Postgres or Clickhouse

• Adding Redis queues and a worker container to our stack to execute async tasks

• Come up with a new architecture for our ingestion pipeline with the goal to increase throughput and cut cost

• Explore different CH schemas and materialized views and test for different query patterns.

• Re-building our SDKs to use OTEL under the hood

• Write Terraform code to add new infra components

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

• see our tech stack

• see our architecture

• Experience in maintenance of highly reliable and scaling infrastructure

• 3+ years of experience in backend or full-stack development

• Excited about open source software

• Experience with the trade offs of handling large amounts of data

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

• A CS/quantitative degree is preferred

Bonus

• Experience with or interest in SDK design and DX

• ML/AI experience

• Impressive achievements from previous careers or side projects

• Previous startup or founding experience

• 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"

• 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

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

• Project you could have built: Infrastructure Evolution Blog Post

• Our codebase: GitHub Repository

• Ben Kuhn on Impact, Agency and Taste

• Who we are & how we work

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

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).

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.

• 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.