Qdrant

Powering the next generation of AI applications with advanced and high-performant vector similarity search technology. Qdrant is an open-source vector search engine. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more. Make the most of your Unstructured Data!

qdrant.tech

Qdrant

qdrant.tech

HQDE

Team Size113

Open Jobs23

Total Funding$42M

Latest FundraiseUnknown

TL;DR

What they do: Open-source vector database and search engine for low-latency similarity search

Founded: 2021

HQ: Berlin, Germany

Latest known funding: Series A $28M (Jan 2024)

Tech highlight: Implemented in Rust; offers self-hosted and managed cloud/on-prem editions

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Company Overview

Problem Domain

Low-latency similarity search over unstructured data (vector search for AI applications).

Founded

2021

Industry

Software Development

Tech Stack

Rust

Vector search / vector database

Funding Track Record

Pre-seed

€2,000,000

Pre-seed raised prior to seed (amount reported as approximately €2M).

Seed- April 2023

7,500,000

Seed round participation included 42cap, IBB Ventures and angel backers.

Series A- January 2024

28,000,000

Series A included participation from existing investors Unusual Ventures and 42cap.

Investor Signal

“Led by Spark Capital in Series A with participation from Unusual Ventures and 42CAP”

Founders

What we do

Join the Team

Developer Relations Engineer (Europe)

RemoteGermany, DE

Remote • Germany, DE

About Us

Powering the next generation of AI applications with advanced and high-performant vector similarity search technology.

Qdrant is redefining how developers build intelligent applications. As a high-performance vector search engine, Qdrant powers contextual search, RAG systems, AI agents, multi-modal retrieval, and real-time recommendations for teams around the world. Developers rely on Qdrant Cloud, Qdrant Open Source, and our ecosystem to build fast, scalable, production-ready AI applications.

About the Role

As a Developer Relations Engineer, you will be the face and voice of Qdrant in the heart of the world’s most active AI ecosystem. You are part engineer, part educator, and part community builder. Your mission is to empower developers to build sophisticated AI applications using Qdrant through high-quality content, world-class demos, and authentic community engagement.

We view this role as a high-velocity career accelerator. By joining us, you will:

Master the Modern AI Stack: Move beyond being a "user" of AI to becoming an expert in the underlying infrastructure (Vector Search, Rust-based performance, and RAG architecture).
Build an Elite Network: Represent Qdrant at the highest levels of the SF tech scene, collaborating with founders and engineers from LlamaIndex, CrewAI, Google DeepMind, Mistral AI, Neo4j, and more
Establish Thought Leadership: We provide the stage. You will be supported in speaking at premier conferences and publishing content that reaches hundreds of thousands of developers globally.

This is an individual contributor role with ~60% hands-on technical work and ~40% community, content, and speaking.

Tasks

Requirements

Technical Depth: You have a strong coding background in Python, Rust, JavaScript, or Go and a genuine fascination with vector search, embeddings, and LLMs.
Communication Mastery: You can explain the "how" and the "why" of technical architecture with clarity and enthusiasm, whether in writing or on stage.
Local Presence: You are already plugged into (or eager to lead) the local tech community. You thrive in the high-energy environment of the AI engineering scene.

Benefits

Competitive Salary
Remote-first
Paid leave

Come work for the best vector search company on the planet and boost your career in AI!

Seeking candidates who can work from:

Paris
London
Amsterdam
Stockholm
Dublin
Barcelona
Madrid

Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.

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Shape the Product: Act as the direct link between the developer community and our core engineering team, directly influencing our roadmap and feature set.

Building Demos: Develop and maintain open-source "showcase" applications. You’ll build end-to-end RAG pipelines, recommendation engines, and innovative AI search tools that demonstrate Qdrant's power.

Applied Innovation: Conduct research into emerging AI patterns (e.g., Long-context RAG, Agentic workflows) to prototype new Qdrant use cases. You will experiment with cutting-edge embedding models and indexing techniques to define the next "killer app" for vector search.

Content Creation: Produce educational resources that make complex concepts accessible. This includes writing deep-dive technical blog posts, recording video tutorials, and crafting clear, useful tutorials.

Technical Events: Lead Qdrant’s presence at hackathons and workshops, from organizing our own challenges to mentoring developers in the middle of the night as they build their MVPs.

Public Speaking: Deliver compelling presentations and live coding sessions at conferences and workshops that inspire developers to rethink what's possible with vector search.

Community & Social Engagement: Actively participate in the AI developer community on platforms like Discord, X (Twitter), LinkedIn, and GitHub. Be the "first responder" to technical questions and a champion for developer needs internally.

Local Leadership: Host and participate in local and regional meetups, technical mixers, and industry conferences. You will be the primary contact for the local AI scene.

Creative Mindset: You don't just follow tutorials; you create them. You enjoy finding creative ways to show off technical features through code and storytelling.

Autonomy & Empathy: You are a self-starter who can work independently while maintaining deep empathy for the frustrations and successes of the developers you support.