Solutions Architect - Langfuse
C
ClickHouseCloud, Analytics, AI
West Coast, USFull-Time
Salary225,000 - 300,000 USD per year
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Job Details
- Required Skills
- Prompt EngineeringDistributed Systems
Requirements
- Hands-on experience in the LLM observability or AI monitoring space — whether at a vendor or as a practitioner building and operating LLM applications in production
- Technical depth in the modern AI stack — comfortable discussing prompt engineering, RAG architectures, evaluation frameworks, token economics, and the data infrastructure that supports them
- Customer-facing experience — pre-sales, solutions engineering, developer advocacy, or technical account management
- Strong foundation in data infrastructure — experience with analytical databases, distributed systems, and cloud infrastructure
- Familiarity with ClickHouse, Postgres, or columnar databases is a strong plus
- Open source orientation — understand how open source communities work, how developer trust is earned, and how to contribute authentically rather than just promote
Responsibilities
- Lead technical evaluations with AI engineering teams considering ClickHouse as their observability data store, from initial architecture review through POC and production deployment
- 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
- Design and deliver reference implementations, schema designs, and ingestion patterns optimized for LLM trace data at scale
- Source and qualify pipeline directly through ecosystem relationships and community engagement
- Partner with ClickHouse AEs to progress and close opportunities within the AI and LLM observability segment
- 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
- Create technical content — blog posts, tutorials, reference architectures, and demo environments — that showcases ClickHouse| Langfuse as the analytics backbone for LLM observability workloads
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