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QdrantQD

Senior Customer Support Engineer (India-Based Candidates Only)

Qdrant is an open-source vector database that delivers high-performance vector similarity search capabilities, catering to the evolving needs of the AI landscape.

Qdrant

Employee count: 51-200

United States only

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Location: India (Applications from outside India will be automatically discarded)
Type: Full-Time – Remote

Qdrant is an Open-Source Vector Database: https://github.com/qdrant/qdrant

We help businesses harness modern AI technologies by providing state-of-the-art neural search capabilities at scale. Our flagship product is the open-source Qdrant vector database, and we also offer a managed cloud solution for enterprise use.

We’re looking for a hands-on Customer Support Engineer who is eager to work closely with customers and solve complex technical issues. This is a high-impact opportunity for someone who leads by example and is excited to help shape the future of a growing support function in a fast-paced AI infrastructure startup.

Tasks

  • Provide direct technical support to our customers, addressing issues related to our vector database and SaaS platform.
  • Investigate and troubleshoot complex issues involving infrastructure, cloud, and database layers.
  • Collaborate with engineering and platform teams to resolve customer problems and influence product improvements.
  • Build and improve internal tooling for support workflows and observability.
  • Participate in the on-call rotation to ensure timely response to critical issues.
  • Create and maintain clear, useful internal and customer-facing documentation.
  • Lead by example through excellent technical work, initiative, and collaboration with stakeholders.

Requirements

Must Have:

  • Strong experience in a customer-facing support or infrastructure role.
  • Proficiency in Python or similar language
  • Good understanding of Kubernetes and managing workloads.
  • Experience with cloud environments (AWS, GCP, or Azure).
  • Excellent communication and collaboration skills across technical and non-technical audiences.
  • Familiarity with vector databases or similar search technologies.
  • A proactive, problem-solving mindset and willingness to take ownership.
  • Based in the EMEA region (mandatory).

Nice to Have:

  • Experience troubleshooting complex issues with customer production deployments.
  • Experience with observability tools and automating support workflows.
  • Understanding of DevOps tools and practices.

Benefits

  • A remote-first, international team working on cutting-edge AI infrastructure.
  • A competitive salary with additional perks.
  • Flexible working hours and async-friendly culture.
  • Regular team offsites and virtual events.
  • Hardware budget – choose your own setup.

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About Qdrant

Learn more about Qdrant and their company culture.

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At Qdrant, we are pioneering a new era in data management by building the most efficient, scalable, high-performance vector database available. Established in 2021, our mission arose from the need to address the challenges of managing vast amounts of unstructured data that includes images, audio, video, and text. Traditional methods of data retrieval often fall short, particularly when it comes to handling this multifaceted data landscape. Our vector database is specifically designed to efficiently manage high-dimensional data, thus enabling advanced AI applications to flourish.

Since our inception, we have been thrilled to witness tremendous growth within our community, boasting thousands of users and millions of downloads of our open-source solution. Qdrant powers an impressive range of applications across the AI sector, from innovative startups to established enterprises. We owe this success to our dedicated leadership team, encompassing CEO and co-founder Andre Zayarni, and CTO and co-founder Andrey Vasnetsov, who together strive to enhance our offerings and ensure we remain at the forefront of the technology curve. We invite you to join us in creating the future of AI with our advanced vector similarity search technology, which is built for cloud-native scalability and high availability.

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