Product Engineer (Integrations)

Langfuse
EuropePosted 29 October 2025

Job Description

Product Engineer (Integrations) ABOUT LANGFUSE Open Source LLM Engineering Platform that helps teams build useful AI applications via tracing, evaluation, and prompt management (mission https://tracking.us.nylas.com/l/6d586a21a6fc4e1a8aacc7eb75882b72/0/82383757e54352130f65066e1b2fc4708aacab7897561bcb8000fe4c8a9c6a21?cache_buster=1761124921, product https://tracking.us.nylas.com/l/6d586a21a6fc4e1a8aacc7eb75882b72/1/b9fba3a93b6ffcc0f99ecda62767a17cc437fe8fe0b16181d1c43c1391212e3d?cache_buster=1761124921). 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 https://langfuse.com/handbook/how-we-work/principles). WHY INTEGRATIONS ENGINEERING AT LANGFUSE Your work puts Langfuse into developers’ hands. Our SDKs are downloaded 26M+ times per month, and for many developers the first thing they touch is an integration — a few lines of code that connect their favorite framework to Langfuse. When that experience is seamless, they’re wow’ed. When it’s not, we might have lost them. You’ll own that critical first impression across 40+ framework integrations. You’ll live at the frontier of LLM application development. The AI framework ecosystem moves fast — new agent frameworks, orchestration libraries, and model providers emerge every week. You’ll be among the first to instrument them, giving you unmatched exposure to how cutting-edge AI applications are built. The developers you serve are some of the most ambitious software engineers in the world, and working closely with them will make you an expert on LLM engineering yourself. Everything you build is open source and immediately visible. All Langfuse integrations are MIT-licensed. When you ship a new integration or improve an existing one, thousands of developers benefit the same day — and they’ll tell you about it in GitHub issues, on Twitter, and in our community channels. WHAT YOU’LL DO - Build and maintain framework integrations. Langfuse integrates with 40+ frameworks and model providers: OpenAI SDK, Vercel AI SDK, LangChain, LlamaIndex, Pydantic AI, OpenAI Agents, CrewAI, Amazon Bedrock AgentCore, LiveKit, and many more. You’ll own these integrations end-to-end — from initial implementation to ongoing maintenance as frameworks evolve. When a new framework gains traction, you’ll be among the first to instrument it. - Design new integration patterns for emerging frameworks. When a framework or a new agent orchestrator appears, you’ll evaluate it, design the right instrumentation approach (callback handler, decorator, OTEL auto-instrumentation, or a combination), build the integration, write the docs, and ship it. You’ll develop strong opinions on what makes a great integration experience. - Contribute to the core SDKs. While integrations are your primary focus, your work will surface needs in our Python and TypeScript SDKs. You’ll contribute improvements to the core SDK when your integration work demands it — whether that’s a new hook point, better context propagation, or performance optimizations. - Write documentation and integration guides. At Langfuse, docs are part of our core product. When you ship a new integration, the guide ships with ... (truncated, view full listing at source)
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