Solutions Architect - Langfuse

Details

ClickHouse acquired Langfuse (an open source LLM observability platform) and is looking for a Langfuse Solutions Architect to be the dedicated technical presence in the LLM observability space. The role sits at the intersection of community, pre-sales, and technical advisory and focuses on opening doors through the Langfuse community, deepening relationships with AI engineering teams, and helping them adopt the combined ClickHouse + Langfuse platform for real-time analytics and LLM observability workloads.

Responsibilities

Pre-Sales & Technical Advisory

• 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 LLM application stacks, trace volumes, evaluation workflows, and query patterns and map those requirements to ClickHouse + Langfuse capabilities
• Work across all levels of customer organizations, from individual contributors building LLM pipelines to CTOs making infrastructure decisions
• Design and deliver reference implementations, schema designs, and ingestion patterns optimized for LLM trace data at scale

Pipeline & Revenue Contribution

• Source and qualify pipeline directly through ecosystem relationships and community engagement — 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

Ecosystem & Community Presence

• Serve as ClickHouse's primary technical voice in the Langfuse community — contributing to forums, engaging on GitHub, participating in events, and building 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

Requirements

• Hands-on experience in the LLM observability or AI monitoring space — either at a vendor or as a practitioner building and operating LLM applications in production
• Technical depth in the modern AI stack: prompt engineering, RAG architectures, evaluation frameworks, token economics, and the supporting data infrastructure
• Customer-facing experience in pre-sales, solutions engineering, developer advocacy, or technical account management
• Strong foundation in data infrastructure, including analytical databases, distributed systems, and cloud infrastructure. Familiarity with ClickHouse, Postgres, or columnar databases is a strong plus
• Open source orientation and understanding of how open source communities work and how to contribute authentically

Compensation

• Typical starting salary for this role in the United States: $225,000 - $275,000 USD
• Typical starting salary for this role in US Premium Markets (e.g., San Francisco Bay Area, New York City Metro): $275,000 - $300,000 USD

These ranges reflect what the company believes to be the minimum and maximum pay for this role at the time of posting. Actual compensation may be higher or lower and is dependent on factors such as experience, qualifications, and location.

Perks

• Flexible work environment; ClickHouse is a globally distributed, remote-friendly company
• Employer contributions towards healthcare
• Equity (stock options) for new team members
• Flexible time off in the US and generous entitlement in other countries
• $500 home office setup for remote employees
• Global company-wide offsites and opportunities for in-person connection

Culture & Equal Opportunity

• As a scaling startup, the role will help shape company culture
• ClickHouse provides equal employment opportunities and prohibits discrimination and harassment

Privacy

• Applicant privacy statement is provided in the posting