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.
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 OwnThe 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.
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.
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).
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!
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Skills Required
- 6+ years of product marketing experience
- At least 4 years marketing developer-facing or data infrastructure products such as databases, search, APIs, cloud infrastructure, or AI/ML tooling
- Experience owning product marketing for an enterprise-led sales motion
- Experience shaping activation, upgrades, and sales-assisted deals, with measurable metrics
- Experience at a startup or scale-up owning a product marketing area end to end
- Experience building sales enablement that changed how a team sold
- Comfort participating in customer calls and working with account executives
- Technical ability to run a quick start, read code samples, and explain keyword, vector, and hybrid search tradeoffs
- Experience building AI tools used by others and evaluating output quality
- Experience working alongside a Developer Relations team
- Experience with partner and cloud marketplace marketing, including AWS, Google Cloud, or Azure
What We Do
Qdrant is an open-source vector database and search engine designed for AI applications. It enables fast, scalable similarity search for unstructured data, supporting use cases like semantic search, recommendation engines, and RAG systems. Built in Rust, it provides high-performance retrieval with metadata filtering and real-time updates, serving as a critical infrastructure component for developers building AI-powered platforms.








