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As a Senior Cloud Infrastructure Engineer, you will manage Langfuse's cloud operations on AWS, ensuring high uptime and performance while optimizing costs. You'll own the observability setup with Datadog, automate processes, and make self-hosting seamless for users. You'll also focus on scaling infrastructure and maintaining security compliance.

As a Product Engineer, you'll build and maintain integrations with various AI frameworks, design new patterns, contribute to core SDKs, and engage with the developer community to enhance the LLM application experience.

Design and build critical IAM and billing infrastructure for Langfuse, enabling secure user management and accurate usage-based invoicing. Collaborate with teams to ensure seamless integration of authentication and authorization systems, while supporting self-hosted deployments for enterprise clients.

Own and ship full-stack product features end-to-end for an open-source LLM observability platform: design specs, implement frontend and backend work (TypeScript/React, ClickHouse, Python), talk to users, write docs, and improve developer experience while collaborating in a small engineering team.

Build and maintain growth-focused product features and analytics. Own data stack (PostHog, BigQuery, DBT, Metabase), run experiments to improve funnel and activation, ship full‑stack improvements across frontend and backend, and create growth loops to increase adoption and expansion.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Own and improve Langfuse SDKs (Python and TypeScript), ensuring reliability, performance, API design, integrations with AI frameworks, OpenTelemetry support, documentation, and developer experience.