Solutions Engineer (EMEA)
WFA Digital Insight
The demand for AI infrastructure specialists has grown exponentially, with a 25% increase in job openings over the past year. As companies like Qdrant pioneer the retrieval infrastructure layer for modern AI, the need for skilled solutions engineers who can navigate the complexities of vector search engines and HubSpot integrations has never been more pressing. With the right combination of technical expertise and business acumen, candidates can capitalize on this trend. Qdrant's recent $50M Series B funding is a testament to the company's potential for growth and innovation. Before applying, candidates should be prepared to demonstrate their understanding of AI infrastructure, vector search, and semantic retrieval, as well as their ability to communicate complex technical concepts to both technical and non-technical stakeholders.
Job Description
About the Role
As a Solutions Engineer at Qdrant, you will play a critical role in driving the company's European field team forward, working closely with senior engineers and account executives to deliver cutting-edge AI infrastructure solutions to clients. Your day-to-day responsibilities will involve supporting technical evaluations, building demo environments, and responding to technical questions from prospective customers. You will also have the opportunity to work directly with the product and engineering teams to surface customer feedback and shape the company's roadmap.The role is based in Berlin, and you will be expected to work within European business hours. As a key member of the technical field team, you will be responsible for owning technical engagements with customers, learning how enterprise AI systems are designed and sold, and contributing to the development of battlecards, technical guides, and internal knowledge bases.
Qdrant's vector search engine, written in Rust, is already being used by notable companies such as Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom. As a Solutions Engineer, you will have the opportunity to work with these companies and help them unlock the full potential of Qdrant's technology.
What You Will Do
- Support technical evaluations and proof-of-concept builds alongside senior Solutions Engineers and Account Executives, helping prospects test Qdrant against their real workloads.
- Build demo environments, sample integrations, and reference architectures that showcase Qdrant's performance advantages in RAG pipelines, semantic search, and agentic systems.
- Respond to technical questions from prospective customers, translating infrastructure requirements into working solutions.
- Learn the competitive landscape across vector search and AI infrastructure, and contribute to battlecards, technical guides, and internal knowledge bases.
- Represent Qdrant in online communities, developer forums, and European tech events as you build your own technical presence.
- Work directly with the product and engineering teams to surface customer feedback that shapes the roadmap.
- Collaborate with senior engineers and account executives to develop and deliver customized solutions for clients.
- Develop and maintain a deep understanding of Qdrant's technology and its applications in various industries.
- Provide technical training and support to customers, ensuring they are able to effectively utilize Qdrant's solutions.
What We Are Looking For
- 1 to 3 years of experience in software engineering, data engineering, solutions engineering, or a closely related technical role.
- Comfortable writing and reading code (Python required; experience with other languages is a plus).
- Genuine curiosity about AI infrastructure: you've built something with LLMs, embeddings, or vector search, even if just as a side project.
- Strong communicator in English, written and verbal. You can explain a technical tradeoff clearly to someone who wasn't in the room when it was made.
- Self-directed: you're comfortable figuring things out, asking good questions, and closing your own knowledge gaps without waiting to be told.
- Based in Europe and available to work within European business hours.
- Experience with cloud infrastructure, data pipelines, or distributed systems is a plus.
- Familiarity with RAG, agentic AI frameworks (LangChain, LlamaIndex, CrewAI), or embedding models is desirable.
Nice to Have
- Exposure to vector search, approximate nearest neighbor algorithms, or semantic retrieval.
- Experience with data pipelines, cloud infrastructure, or distributed systems.
- Familiarity with RAG, agentic AI frameworks (LangChain, LlamaIndex, CrewAI), or embedding models.
- Background in a customer-facing technical role (support engineering, developer advocacy, technical writing).
Benefits and Perks
- Equity with meaningful upside in a well-capitalized, fast-scaling company.
- Medical, dental, and vision coverage.
- Hardware budget: choose your own setup.
- Annual learning and conference budget.
- Flexible hours, async-friendly culture, and regular team offsites.
- Opportunity to work with cutting-edge AI technology and contribute to the development of Qdrant's vector search engine.
- Collaborative and dynamic work environment with a team of experienced engineers and technologists.
- Professional development opportunities, including training and mentorship programs.
- Access to a network of professionals in the AI and technology industry.
How to Stand Out
- Develop a strong understanding of AI infrastructure, vector search, and semantic retrieval before applying.
- Showcase your ability to communicate complex technical concepts to both technical and non-technical stakeholders.
- Highlight any experience you have with cloud infrastructure, data pipelines, or distributed systems.
- Be prepared to demonstrate your problem-solving skills and ability to think critically.
- Research Qdrant's technology and its applications in various industries to demonstrate your interest and enthusiasm for the company's mission.
- Prepare to talk about your experience with Python and other programming languages.
- Be ready to discuss your experience working in a customer-facing technical role, if applicable.
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