Technical Customer Support Engineer, AI Infrastructure & Observability - EMEA
ClickHouse is hiring a Technical Customer Support Engineer, AI Infrastructure & Observability - EMEA. Level rates it ; you can apply on ClickHouse.
Level's read on this job
- On Level's scale, this customer service role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting allows some remote work.
- Tools and skills the posting cites include OpenAI, Anthropic and LangChain.
- Level classifies it as a mid-level role.
- Level lists 202 other open roles at ClickHouse.
AI in this role
Provide technical customer support for AI infrastructure, tracing, and evaluation tools like Langfuse and ClickHouse.
ClickHouse welcomed Langfuse, the leading open-source platform for tracing, evaluation, and observability, to strengthen its position in the AI infrastructure and LLM observability ecosystem. With ClickHouse and Langufuse scaling to power enterprise AI workloads, we're growing our support team to provide a world-class experience for our expanding customer base, with unified expertise across database infrastructure and AI observability.
We are seeking a Technical Customer Support Engineer to join our global Support Engineering team in a hybrid role spanning both ClickHouse and Langfuse ecosystems. In this position, you will support customers across EMEA and globally in the Americas and APJ when support is needed or coverage overlaps. You’ll be handling technical issues and solutions, ranging from core ClickHouse database requests to helping thousands of AI product teams succeed with tracing & evals in Langfuse. You will own a wide array of responsibilities, including front-line troubleshooting, community support, pre- and post-sales technical activities, and partnering on deeply technical POCs, and suggesting improvements to how we do things in Support at ClickHouse.
What You'll Be Doing
Supporting and guiding our ClickHouse & Langfuse users, customers, and prospects via cases, chat, Slack, community, and phone calls, delivering high-touch guidance within required Service Level Agreements (SLAs) as part of a global on-call coverage rotation.
Develop solutions based on ClickHouse Cloud and ClickHouse open-source that can be shared with our users, community, and customers via documentation, knowledge base, blogs, meetups, webinars, and training.
Work closely with our global Support Services, Engineering, Go-to-Market, and Product Management teams to help define the functionality required by users and customers.
Assist with mentoring, training, and sharing your knowledge with colleagues, users, and customers.
Escalate bugs to product engineering and close the loop with the customer once shipped.
Go through deep technical integration/implementation questions together with our customers and directly within their codebases.
Build strong, trusted relationships with colleagues, customers, and partners across the developer ecosystem
What You Bring
For ClickHouse & Core Infrastructure:
Databases & OLAP Systems: Hands-on experience with databases, OLAP, or distributed systems (ClickHouse, SQL engines, or cloud-native SaaS infrastructure).
Systems Fundamentals: Strong software engineering fundamentals (CS, Data Science degree, or comparable hands-on project experience) with comfort reading code, working with data pipelines (e.g., Kafka, Spark), or debugging cloud infrastructure (AWS/GCP/Azure).
Distributed & Operational Rigor: Comfort working in a global, remote-first team aligned to SLA coverage, on-call needs, and async communication.
For Langfuse & AI Observability:
LLM Tooling & Application Dev: Genuine curiosity for LLM application development with hands-on experience building, debugging, or evaluating LLM-powered products using frameworks like Python, TypeScript, LangChain, LlamaIndex, or Vercel AI SDK.
Tracing, Evals & Developer Tooling: Familiarity with LLM observability/eval tooling, prompt workflows, model provider APIs (OpenAI, Anthropic), or OpenTelemetry-style tracing to unblock AI-product teams.
Technical Support & Communication: Strong written communication across registers. You have concise Slack troubleshooting, clear long-form docs/guides, and a customer-first mindset to unblock engineers.
Bonus Points
Experience with OSS and open-source technologies, as a user, community member, or contributor
Experience with ClickHouse
Experience with Langfuse specifically, or with LLM observability/eval tooling more broadly.
Experience with AWS, GCP, or Azure.
Experience with data pipeline technologies such as Kafka, Kinesis, Spark, or RabbitMQ.
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
Technical Customer Support Engineer, AI Infrastructure & Observability - EMEA at ClickHouse rates 65 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.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in customer service jobs at this level
Pay
- Typical customer service job
- $100k
This posting doesn't list pay. Use the typical customer service figure when pay comes up. See customer service jobs
Questions you could be asked
- Tell me about a project where technical support was part of your work. What did you do?
- Tell me about a project where observability was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where troubleshooting was part of your work. What did you do?
- Walk me through how you've used OpenAI in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Technical Support, Observability, Distributed Systems, Troubleshooting, and OpenAI. 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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