At a Glance
- Tasks: Lead technical evaluations and engage with AI engineering teams to optimise LLM applications.
- Company: Join ClickHouse, a leader in real-time analytics and LLM observability.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with a focus on community engagement and technical advisory.
- Why this job: Be at the forefront of AI observability and make a significant impact in the tech community.
- Qualifications: Experience in AI monitoring, strong data infrastructure knowledge, and customer-facing skills.
The predicted salary is between 70000 - 90000 € per year.
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; capable of navigating technical conversations with real stakes and building 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 — understanding how open source communities work, how developer trust is earned, and how to contribute authentically rather than just promote.
What the job involves
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.
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 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 application 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 as the analytics backbone for LLM observability workloads.
Solutions Architect (LangFuse EMEA) in London employer: Deepstreamtech
At ClickHouse, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Solutions Architect for LangFuse in the EMEA region, you will have the opportunity to work at the forefront of AI observability, engaging with cutting-edge technology while contributing to a vibrant open-source community. We offer robust employee growth opportunities, competitive benefits, and a supportive environment that encourages professional development and meaningful contributions to the AI landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Solutions Architect (LangFuse EMEA) in London
✨Tip Number 1
Get your networking game on! Connect with folks in the AI observability space, especially those involved with Langfuse and ClickHouse. Attend meetups, webinars, or online forums to build relationships and show your passion for the field.
✨Tip Number 2
Show off your expertise! Prepare to discuss your hands-on experience with LLM applications and the modern AI stack. Be ready to dive into technical conversations about prompt engineering and data infrastructure – this is your chance to shine!
✨Tip Number 3
Don’t just apply – engage! When you apply through our website, make sure to follow up with a personal message. Share your thoughts on how you can contribute to the Langfuse community and enhance the ClickHouse + Langfuse story.
✨Tip Number 4
Create some buzz around your skills! Write blog posts or create content that showcases your understanding of LLM observability and analytics. This not only demonstrates your knowledge but also helps you connect with others in the community.
We think you need these skills to ace Solutions Architect (LangFuse EMEA) in London
Some tips for your application 🫡
Show Your Technical Depth:When you're writing your application, make sure to highlight your hands-on experience with LLM observability and the modern AI stack. We want to see that you can comfortably discuss prompt engineering and data infrastructure, so don’t hold back on those details!
Customer-Facing Experience Matters:Don’t forget to mention any customer-facing roles you've had, like pre-sales or solutions engineering. We’re looking for someone who can navigate technical conversations and build trust with engineering teams, so share examples of how you've done this in the past.
Emphasise Your Open Source Orientation:Since we value open source contributions, let us know about your understanding of open source communities. Share any experiences you have with contributing authentically, as this will show us you get how developer trust is built.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, we love seeing applications come directly from our community!
How to prepare for a job interview at Deepstreamtech
✨Know Your AI Stack
Make sure you’re well-versed in the modern AI stack, especially around LLM observability. Brush up on prompt engineering, RAG architectures, and token economics. Being able to discuss these topics confidently will show that you’re not just familiar with the theory but can apply it practically.
✨Showcase Your Customer-Facing Experience
Prepare examples from your past roles where you’ve navigated technical conversations with engineering teams. Highlight how you built trust and communicated complex ideas clearly. This is crucial for a role that involves pre-sales and technical advisory.
✨Engage with the Open Source Community
Familiarise yourself with how open source communities operate. Be ready to discuss your contributions or experiences within these spaces. This will demonstrate your understanding of developer trust and how to authentically engage with the Langfuse community.
✨Prepare for Technical Evaluations
Anticipate questions about how you would lead technical evaluations with AI engineering teams. Think through potential architecture reviews and POC scenarios. Showing that you can map customer requirements to ClickHouse capabilities will set you apart.
