---
title: 'Cloud Infrastructure Cost Analyst (FinOps) at Qdrant'
canonical: 'https://feeny.ai/job/cloud-infrastructure-cost-analyst-finops-qdrant-emea-5b03t5v7pk4q'
type: 'job'
last_seen: '2026-09-06'
---

# Cloud Infrastructure Cost Analyst (FinOps) at Qdrant

- **Company:** Qdrant
- **Location:** EMEA
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-04-27
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/qdrant.tech/c13adc26-fdfd-428a-b234-de2db5e0283e

## Job description

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.

We are looking for a Cloud Infrastructure Cost Analyst to help us understand, forecast, and optimize the cost structure of our cloud-based products.

This role sits between engineering, finance, and data analytics. You will work closely with our Cloud Engineering team to understand how architectural decisions impact infrastructure cost and help the company make better data-driven decisions around scaling, resources, pricing, and usage.

You should be comfortable diving into cloud infrastructure concepts, analyzing usage data, and building tools and reports that help engineering, finance, and sales understand the economics of our platform.

## WHAT YOU WILL OWN

- Analyze cloud usage and infrastructure spend to understand the main cost drivers across our platform.
- Build and maintain reports on infrastructure cost (e.g. free vs paid tier usage, POC environments, product-level cost).
- Work closely with the Cloud Engineering team to understand how architecture and resource usage affect cost.
- Develop models to estimate cost per customer, feature, or workload.
- Forecast infrastructure spend based on usage trends and upcoming changes in our architecture.
- Identify opportunities for cost optimization (e.g. savings plans, resource sizing, usage patterns).
- Build internal dashboards and simple tools to make cloud cost data accessible to engineering, finance, and sales.
- Support internal teams with data for pricing, deal modeling, and infrastructure planning.

## WHO YOU ARE

- Strong analytical skills and experience working with Python and SQL.
- Experience analyzing large datasets and building reports or dashboards.
- Familiarity with public cloud platforms (AWS, GCP, or Azure) and a basic understanding of infrastructure components such as compute, load balancing, and serverless workloads.
- Ability to translate technical usage data into cost models, forecasts, or business insights.
- Comfortable working with engineers and understanding how cloud architecture and resource usage affect cost.
- Experience working with modern data platforms (e.g. Snowflake or similar).

## NICE TO HAVE

- Experience with cloud cost analysis, FinOps, or infrastructure cost modeling.
- Experience working in cloud engineering, DevOps, or infrastructure-heavy environments.
- Familiarity with cloud billing tools or cost management tools (AWS Cost Explorer, GCP Billing, etc.).
- Experience with forecasting, budgeting, or usage modeling.

## 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!

FOR INFORMATION ON HOW WE HANDLE YOUR PERSONAL DATA, PLEASE REFER TO OUR RECRUITMENT PRIVACY POLICY https://qdrant.tech/legal/recruitment-privacy-policy/

## #LI-REMOTE

## About Qdrant

## Company Overview
- **One-liner**: Qdrant provides an open-source, high-performance vector search engine and database built in Rust, powering AI retrieval applications.
- **Entity Type**: Private (Series B)
- **Headquarters**: Berlin, Germany
- **Founded**: 2021
- **Founders**: Andrey Vasnetsov (CTO) and Andre Zayarni (CEO)

## Core Business
- **Primary industry/industries**: Vector database software, AI infrastructure, search and retrieval.
- **Target customers**: B2B – enterprises, AI/ML teams, developers building semantic search, RAG, recommendation systems, anomaly detection, and AI agents.
- **Mission or purpose statement**: "Powering the next generation of AI applications with advanced and high-performant vector similarity search technology."

## Products & Services
- **Qdrant Cloud**: Fully managed SaaS on AWS, GCP, or Azure with auto-sharding, high availability, and native cloud inference for embeddings.
- **Qdrant Hybrid Cloud**: Bring your own Kubernetes with decoupled control and data planes for flexible on-prem or multi-cloud deployments.
- **Qdrant Private Cloud**: Air-gapped, compliant deployments for maximum data control.
- **Qdrant Edge (Beta)**: Lightweight, low-latency vector search for edge devices.
- **Core Engine**: Open-source Rust-based vector database with SIMD, custom Gridstore engine, real-time indexing, memory-efficient storage (quantization up to 64x reduction), and built-in support for dense/sparse vectors, hybrid search, multivector, and reranking (ColBERT, MMR).
- **Developer Tools**: REST and gRPC APIs, official clients (Python, JavaScript), built-in Web UI for visualization, and integration with Prometheus/Grafana/Datadog.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Total funding of **$88.3M** across five rounds (Pre-Seed, Seed, Series A, Series B, and a venture round). Annual revenue estimated at **$1.0M**.
- **Notable Investors/Partners**: Lead investors include AVP (Series B), Spark Capital (Series A), Unusual Ventures (Seed), 42CAP (Pre-Seed). Other investors not fully named.
- **Growth Signals**: 60% headcount growth year-over-year (88 employees as of mid-2025); 30k+ GitHub stars; 60k+ community members; 30 active job postings; expansion to 23 countries; SOC2 & HIPAA compliant.

## Competitive Advantages
- **Pure Rust implementation** with SIMD and a custom storage engine (Gridstore) – no wrappers, no bolt-ons, delivering high performance and low latency.
- **Real-time indexing** – new vectors are searchable immediately without full index rebuilds.
- **Memory-efficient storage** using asymmetric, scalar, and binary quantization (up to 64x memory reduction).
- **Hybrid search** (dense + sparse) with built-in BM25, SPLADE++, miniCOIL, and ColBERT reranking.
- **Filtering during HNSW traversal** – no pre/post-filtering, high recall under complex conditions.
- **Enterprise-grade security** (RBAC, SSO/SAML/OIDC, multitenancy, private networking, air-gapped options).
- **Flexible deployment** – cloud, hybrid, private, edge, on-prem.

## Strategic Focus
- **Current priorities**: Scaling enterprise adoption of AI retrieval; deepening cloud platform capabilities (native inference, managed services); expanding edge and hybrid deployment options; improving developer experience with multivector and reranking features.
- **Direction for growth**: Becoming the go-to vector database for production-grade AI applications, from RAG agents to recommendation systems.

## Why Work Here
- **Culture highlights**: Open-source DNA with a strong engineering ethos; high-growth environment (60% YoY headcount); distributed team across 23 countries (US, Germany, Spain, France, India, UK, etc.).
- **Remote/hybrid policy**: Hybrid model for Berlin HQ (some roles listed as hybrid); many positions are posted as EMEA or remote-friendly.
- **Notable perks**: Work on cutting-edge AI infrastructure with Rust; contributing to a popular open-source project (30k+ GitHub stars); opportunities to shape a rapidly scaling product.
- **Engineering culture**: Heavy emphasis on performance and first-principles optimization; small, focused teams with high ownership (88 employees); recent VP of Engineering search signals expansion in technical leadership.
- **Active hiring**: 30 open positions across engineering, cloud infrastructure, FinOps, marketing, sales, and technical success.

## Sources
1. [Qdrant Website](https://qdrant.tech/)
2. [Qdrant Careers Page on Ashby](https://jobs.ashbyhq.com/qdrant.tech)
3. [Qdrant About Page](https://qdrant.tech/about-us/)
4. [Qdrant LinkedIn Company Page](https://www.linkedin.com/company/qdrant)
5. [Qdrant GitHub Repository](https://github.com/qdrant)

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