Level

ClickHouse

AI Engineering Solutions Architect

AI in this role

prompt-engineeringrag

About the Role

AI applications are being built faster than teams can monitor, debug, or trust them. ClickHouse recently acquired Langfuse — the leading open source LLM observability platform — making it a core part of the ClickHouse product stack. Together, ClickHouse and Langfuse offer engineering teams the most powerful combination in the market: real-time, high-performance analytics infrastructure paired with best-in-class LLM tracing, evaluation, and observability tooling. This role sits at the center of that combined story.

We're looking for a Langfuse Solutions Architect who is already embedded in the AI observability ecosystem — someone who understands how engineering teams instrument and evaluate LLM applications, and can credibly represent the full ClickHouse + Langfuse platform to the teams that need it most.

This is not a generalist SA role. You'll be our dedicated technical presence in the LLM observability space — opening doors through the Langfuse community, deepening relationships with AI engineering teams, and helping them get the most out of a platform that now spans from raw data infrastructure to production LLM monitoring. You'll work at the intersection of community, pre-sales, and technical advisory, and you'll be the person who makes the ClickHouse + Langfuse stack the obvious choice for teams building serious AI applications.

What You'll Be Doing

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 their LLM application stack, trace volumes, evaluation workflows, and query patterns — and map those requirements to ClickHouse | Lanfguse 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 — 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

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 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

What You Bring

  • 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

#LI-CL1

Perks

  • Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries.

  • Healthcare - Employer contributions towards your healthcare.

  • Equity in the company - Every new team member who joins our company receives stock options.

  • Time off - Flexible time off in the US, generous entitlement in other countries.

  • A USD$500 Home office setup if you’re a remote employee.

  • Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.

Culture - We All Shape It

As part of a rapidly scaling start-up, you will be instrumental in shaping our culture.

Are you interested in finding out more about our culture? Learn more about our values here. Check out our blog posts or follow us on LinkedIn to find out more about what’s happening at ClickHouse.

Equal Opportunity & Privacy

ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Please see here for our Privacy Statement.

How we rate this

AI Engineering Solutions Architect at ClickHouse rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRAG

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering and RAG. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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