Solutions Architect - Langfuse
For roles based in the United States, the typical starting salary range for this position is listed above. In certain locations, such as the San Francisco Bay Area and the New York City Metro Area, a premium market range may apply, as listed. Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 20 countries.Full-Time
Salary225,000 - 300,000 USD per year
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Job Details
- Required Skills
- ClickhousePostgresPrompt 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 — you're 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. You've navigated technical conversations with real stakes and know how to build trust with engineering teams
- 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 — you 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 — this role is expected to open doors, not just walk through them
- Partner with ClickHouse AEs to progress and close opportunities within the AI and LLM observability segment
- Advocate internally for product improvements and integration enhancements that strengthen the ClickHouse + Langfuse story
- 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
- Develop relationships with the Langfuse core team and ecosystem partners to identify joint GTM opportunities and integration improvements
- 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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