---
title: 'Senior Product Marketing Manager (US) at Qdrant'
canonical: 'https://feeny.ai/job/senior-product-marketing-manager-us-qdrant-united-states-jmbbg4msja8s'
type: 'job'
last_seen: '2026-11-08'
---

# Senior Product Marketing Manager (US) at Qdrant

- **Company:** Qdrant
- **Location:** United States
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-10-27
- **Last confirmed live:** 2026-11-08
- **Apply:** https://jobs.ashbyhq.com/qdrant.tech/1ed9f01f-12a1-4618-82f6-c33bb6be07dd

## 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.

The Team and Your Impact As a Senior Product Marketing Manager, you'll join our Product Marketing team and report to our Director of Product Marketing, working day to day with DevRel, Growth, Sales, Partnerships, and Product. Most of our customers find Qdrant before we find them. An engineer runs the open-source engine, spins up a free Qdrant Cloud cluster, and ships a prototype. Your job is to make sure that story ends in a production deployment and a commercial relationship. You'll own how Qdrant is positioned at every step of that path: the docs page, the moment a team upgrades to a paid Cloud cluster, and the enterprise deal where we compete against known competitors. More and more of that research now happens inside AI chats and coding agents, so the messaging and tools you build have to hold up there as well as on a sales call.

## What You Will Own

- The messaging for our self-serve to sales path: what a developer hears while evaluating Qdrant, what changes when they upgrade to a paid Cloud cluster, and what their engineering leader hears when the team brings us in.
- Buyer scenarios for our main entry points, such as moving a self-hosted cluster to Qdrant Cloud, replacing a legacy keyword search engine, or adding retrieval to an AI agent. Each one ships as messaging, a proof point, and an asset that Sales and Growth can use the same week.
- Our competitive program: comparisons, battlecards, and objection handling that stay current with every release, with each claim backed by a benchmark, a customer, or a working demo.
- A win and loss program you design and run yourself, interviewing customers and account executives, and turning what you learn into changed messaging, pricing page copy, and product feedback.
- The AI workflows that scale your work: Claude skills that let account executives and solutions engineers pull the right talk track, comparison, messaging, or case study without waiting for you, and a research loop that turns call notes and interviews into updated assets.
- Launch messaging for Qdrant releases with Product, DevRel, and Growth, so every feature reaches developers through docs and community, and reaches buyers through sales.

## Who You Are

- You have 6+ years in product marketing, with at least 4 of them on a developer-facing or data infrastructure product: databases, search, APIs, cloud infrastructure, or AI and ML tooling.
- You've owned product marketing for an enterprise-led sales motion, ideally in an open source product company. You have shaped activation and upgrade, and built the handoff into a sales-assisted deal. You can name the metrics you moved.
- You've spent time at a start up or scale-up, where you owned a product marketing area end to end without a playbook or a team behind you.
- You've built sales enablement that changed how a team sold, and you're comfortable on customer calls and in front of account executives.
- You're technical enough to earn an engineer's trust: you can run a quick start, read a code sample, and explain the trade offs between keyword, vector, and hybrid search without notes.
- You built AI tools that other people rely on, with the judgment and taste to spot when the output is wrong or not concise.

## Nice To Have

- You've worked alongside a DevRel team and know where product marketing ends and developer advocacy begins.
- Experience with partner and cloud marketplace marketing (AWS, Google Cloud, or Azure).

## 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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