Senior Support Engineer (EMEA)
Qdrant is hiring a Senior Support Engineer (EMEA) for a remote role. Level rates it ; you can apply on Qdrant.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- This is listed as a remote role.
- The posting mentions RAG and AI agents among its tools and skills.
- Level classes it as a senior role.
- Qdrant has 6 other open roles on Level.
AI in this role
Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations.
Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data.
As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI.
The Team and Your Impact
We're hiring a Senior Support Engineer to help customers run Qdrant's vector search engine reliably in production. You'll work Kubernetes-heavy, cloud-native environments every day, investigate hard technical issues, and turn what you learn into tools and workflows that make the whole support function faster. This is a chance to help shape a growing support team at an early-stage AI infrastructure company.
What You Will Own
Provide direct technical support to customers running Qdrant, mostly asynchronous rather than face to face.
Troubleshoot production issues across Kubernetes, cloud infrastructure, networking, storage, and the database layer.
Lead incident investigations and turn recurring problems into documented diagnostics and repeatable fixes, using AI-assisted tooling to speed up triage where it helps.
Partner with engineering and platform teams to resolve customer issues and feed learnings back into the product.
Build and maintain internal tools that make support workflows faster and more observable.
Write and maintain clear documentation for both customers and the internal team.
Lead by example through strong technical work, initiative, and collaboration with stakeholders across the company.
Who You Are
5 or more years in a customer-facing support or infrastructure role, ideally supporting production Kubernetes environments.
Strong, hands-on Kubernetes skills. A Certified Kubernetes Administrator (CKA) credential is a plus.
Proficient in Python or a similar language for scripting and automation.
Experience with Kafka or similar distributed systems.
Comfortable working in AWS, GCP, or Azure.
Solid understanding of database internals and how they behave under production load.
A proactive, ownership-driven mindset. You dig into ambiguous problems without waiting to be asked.
Clear communicator who can translate between technical and non-technical audiences.
Nice to Have
Familiarity with vector search or vector database technologies.
Terraform and infrastructure-as-code experience. Security background is a plus.
Experience with observability tools (for example, Prometheus or Grafana) and automating support workflows.
Why join us
A remote-first, international team working on cutting-edge AI infrastructure.
A competitive salary with additional perks.
Flexible working hours and async-friendly culture.
High ownership and real impact.
Open-source, engineering-driven culture.
Choose your own laptop equipment.
For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy.
Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist.
Come build with us!
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#LI-REMOTE
How we rate this
Senior Support Engineer (EMEA) at Qdrant rates 67 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
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- 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: RAG and AI agents. 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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