Senior Product Engineer
📍 Germany
📍 Spain
📍 France
📍 United Kingdom
📍 Netherlands
📍 Zurich, Switzerland
📍 Munich, Germany
📍 Berlin, Germany
📍 Paris, France
📍 London, United Kingdom
Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
API @ 7
ClickHouse @ 4
Experimentation
LLM @ 3
Machine Learning @ 3
Next.js
OpenTelemetry
PostgreSQL
Python
React @ 4
Redis
Terraform
TypeScript @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Langfuse is an open-source LLM engineering platform for tracing, evaluation, and prompt management, now part of ClickHouse. The engineering team builds developer tools used by more than 2,000 customers, including 19 of the Fortune 50. The role is based in EU time zones and involves spending approximately one week per month in the Berlin office.
Product engineers own features end-to-end, from understanding user problems and writing specifications to implementing, documenting, and publicly launching solutions. The role involves working across the full stack and engaging directly with users through calls, community channels, and support requests.
Responsibilities
- Own features end-to-end, including product discovery, specifications, implementation, documentation, changelog posts, and release communication.
- Build across the full stack, including React, Next.js, ClickHouse analytics, Python and TypeScript SDKs, public documentation, and Terraform modules.
- Talk to users regularly through calls, community channels, and support requests.
- Write public documentation for owned features.
- Ship publicly during Launch Weeks and present completed features to the community.
- Identify what to build, propose solutions through RFCs, and manage delivery independently.
- Consider user experience and technical implementation together.
- Participate in code reviews, collaborative whiteboarding, and a maker-oriented schedule.
Requirements
- Experience building features or entire products from scratch end-to-end.
- Experience building and shipping user-facing products, ideally with TypeScript and React.
- Exposure to data-intensive backends.
- Ability to manage projects independently and develop strong conviction about what to build and how to ship it.
- Strong product and developer-experience judgment, including API design, UI details, and clear documentation.
- Interest in open-source software and enthusiasm for talking to developers about their problems.
- Ability to thrive in a small, accountable, engineering-heavy team.
- A computer science or quantitative degree is preferred.
Bonus Qualifications
- Experience with ClickHouse, analytics databases, or complex data visualizations.
- Founder or early-stage startup experience.
- Contributions to popular open-source projects.
- Machine learning or artificial intelligence experience, or familiarity with the LLM framework ecosystem.
Tech Stack
TypeScript monorepo, Next.js, React, Express workers, PostgreSQL, ClickHouse, Amazon S3, Redis, Terraform, OpenTelemetry, Python SDKs, and TypeScript SDKs. The platform processes terabytes of data per day through its ingestion pipeline and supports data-rich trace visualizations and LLM applications.
Working Environment
The team uses a maker schedule with a Monday priority check-in and Friday demo session. Engineers are trusted to take ownership of their areas, and code reviews are used for mentorship. The company encourages experimentation with AI tooling and workflows.
Process
The hiring process can be completed through an offer letter in less than seven days.