Qdrant Tech Stack

Open-source vector search engine for AI applications

Software Development Berlin, Berlin 51–200 employees Founded 2021 Privately Held

Qdrant is a vector database and search engine built in Rust, deployed across Kubernetes, AWS, GCP, and Azure. The company is actively adopting gRPC and expanding into semantic search, RAG, and agentic AI implementations—reflecting the rapid shift from pure similarity search toward full AI application stacks. Hiring is accelerating across engineering (31 roles) and marketing (9 roles), with a weighted emphasis on senior-level talent, signaling both technical depth needs and a push to formalize developer go-to-market.

Tech Stack 50 technologies

Core StackKubernetes AWS Elasticsearch Pinecone n8n Zapier Go Python Prometheus Grafana OpenTelemetry Ashby Rust RAG Neo4j Snowflake GCP Azure Solr Milvus Google Search Discord X LlamaIndex CrewAI Google DeepMind Mistral AI Cluster API AWS Cost Explorer Lucene+16 more

AdoptinggRPC

What Qdrant Is Building

◆Challenges

Optimizing cloud infrastructure cost
Reducing operational overhead
Technical bottlenecks
Deployment and adoption of ai solutions
Technical health oversight
Crisis management for technical issues
Cost efficiency of cloud infrastructure
Deployment and adoption challenges
Improving cloud infrastructure reliability
Enhancing cost efficiency

▲Active Projects

Own ppc strategy & execution
Technical health checks and architecture reviews
Ai-powered optimization
Implementation lifecycle of semantic search, agentic ai, and rag solutions
Run experiments targeting technical audiences for developer acquisition
Core cloud platform components
Kubernetes operators
Cost allocation models
Cloud infrastructure reliability and cost efficiency
Cost forecasting models

Hiring Activity

Accelerating45 roles · 45 in 30d

Department

Engineering

Marketing

Finance

Seniority

Senior

Mid

Junior

Lead

Staff

Notable leadership hires: Head of Marketing

Company intelligence

Find more companies like Qdrant by tech stack, pain points and active projects

Get started free

About Qdrant

Qdrant develops an open-source vector search engine that enables applications to index, store, and query high-dimensional embeddings in real time. The platform is positioned as infrastructure for AI builders—turning unstructured data and neural network encoders into production search, recommendation, and matching systems. The company operates from Berlin with a distributed hiring footprint across 11 countries (Brazil, United States, Costa Rica, Peru, France, Bulgaria, United Kingdom, India, Germany, Argentina, Colombia). Current focus areas include cloud platform hardening, Kubernetes operational patterns, cost optimization, and commercial implementations of semantic search and retrieval-augmented generation (RAG) solutions.

HeadquartersBerlin, Berlin

Company Size51–200 employees

Founded2021

Hiring MarketsBrazil, United States, Costa Rica, Peru, France, Bulgaria, United Kingdom, India

Frequently Asked Questions

What tech stack does Qdrant use?

Qdrant is built in Rust and runs on Kubernetes. The infrastructure spans AWS, GCP, and Azure. The stack includes Go, Python, Prometheus, Grafana, OpenTelemetry for observability; gRPC is currently being adopted for API optimization.

What is Qdrant working on?

Core projects include cloud platform components, Kubernetes operators, semantic search and RAG implementation frameworks, agentic AI solutions, cloud cost allocation and forecasting models, and developer-focused acquisition experiments.

How this profile is built

Qdrant's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.