Solutions Architect - Langfuse

ClickHouse ClickHouse · Data AI · United States · Go-To-Market

Solutions Architect for Langfuse, an LLM observability platform recently acquired by ClickHouse. The role focuses on engaging with AI engineering teams to understand their LLM application stacks and requirements, and demonstrating how ClickHouse and Langfuse can meet those needs. This involves pre-sales technical advisory, contributing to pipeline generation, and building community presence within the AI observability ecosystem.

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 | Lanfguse capabilities
  3. Work across all levels of customer organizations, from individual contributors building LLM pipelines to CTOs making infrastructure decisions
  4. Design and deliver reference implementations, schema designs, and ingestion patterns optimized for LLM trace data at scale
  5. Source and qualify pipeline directly through ecosystem relationships and community engagement — this role is expected to open doors, not just walk through them

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

Nice to have

  • Familiarity with ClickHouse, Postgres, or columnar databases
  • Open source orientation

What the JD emphasized

  • AI observability ecosystem
  • instrument and evaluate LLM applications
  • LLM observability space
  • LLM application stack
  • trace volumes
  • evaluation workflows
  • LLM trace data at scale
  • ecosystem relationships and community engagement
  • LLM observability segment
  • Langfuse community
  • AI engineers and developers
  • analytics backbone for LLM observability workloads
  • Hands-on experience in the LLM observability or AI monitoring space
  • Technical depth in the modern AI stack
  • Customer-facing experience
  • data infrastructure

Other signals

  • LLM observability platform
  • AI applications
  • real-time analytics, data warehousing, observability, and AI workloads
  • Langfuse community
  • AI engineering teams
  • LLM tracing, evaluation, and observability tooling
  • data infrastructure to production LLM monitoring
  • pre-sales, and technical advisory
  • analytics backbone for LLM observability workloads