Solutions Architect - Langfuse Apj

ClickHouse · Data AI · APJ · Go-To-Market

Solutions Architect for LangFuse (LLM observability platform acquired by ClickHouse), focusing on pre-sales, technical advisory, and community engagement within the AI observability ecosystem. The role involves understanding customer LLM application stacks, designing solutions using ClickHouse and Langfuse, and contributing to pipeline and revenue growth by building credibility with AI engineering teams.

What you'd actually do

  1. Lead technical evaluations with AI engineering teams considering ClickHouse as their observability data store, from initial architecture review through POC and production deployment
  2. Engage directly with data engineers, ML engineers, and platform architects to understand their LLM application stack, trace volumes, evaluation workflows, and query patterns — and map those requirements to ClickHouse capabilities
  3. Source and qualify pipeline directly through ecosystem relationships and community engagement — this role is expected to open doors, not just walk through them
  4. Serve as ClickHouse's primary technical voice in the Langfuse community — contributing to forums, engaging on GitHub, participating in events, and building authentic credibility with AI engineers and developers
  5. Create technical content — blog posts, tutorials, reference architectures, and demo environments — that showcases ClickHouse as the analytics backbone for LLM observability workloads

Skills

Required

  • Hands-on experience in the LLM observability or AI monitoring space
  • Technical depth in the modern AI stack
  • Customer-facing experience
  • Strong foundation in data infrastructure
  • Open source orientation

Nice to have

  • Familiarity with ClickHouse, Postgres, or columnar databases

What the JD emphasized

  • AI observability or AI monitoring space
  • LLM application stack
  • evaluation workflows
  • LLM observability workloads

Other signals

  • LLM observability platform
  • real-time analytics infrastructure
  • best-in-class LLM tracing, evaluation, and observability tooling
  • instrument and evaluate LLM applications
  • data infrastructure that supports them