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Qdrant
Marketing & Sales 1h ago

Growth Marketing Manager at Qdrant

Qdrant
United StatesUnited States
Full-time
Not Disclosed
Mid-Level
VT

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About Qdrant

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.

Role Overview

As a Growth Marketing Manager, you’ll build the systems that make our marketing fast and agile. The tools and tactics in the age of AI change constantly, but what lasts is the underlying system: clean signal data, a scoring model that routes it, and reusable workflows the team can build on. You’ll own that system, using automation and AI to turn a week of work into an hour.

You’ll own the end-to-end demand generation engine that translates market signals and buyer intent into measurable pipeline and revenue impact. You’ll connect audience intelligence, multi-channel campaigns, lifecycle engagement, and sales activation into scalable, repeatable growth motions. You should be able to pull the data, architect a target list, generate the creative, and ship a multi-channel campaign using AI tools and systems, while ensuring every campaign, data point, and automation strengthens the broader growth engine.

What You Will Own

  • The Core Growth Motion: Build reusable campaign systems: templates, automations, and workflows to spin up integrated campaigns without rebuilding from scratch each time. Run priority campaigns end to end, from targeting and messaging through multi-channel execution and pipeline accountability.

  • Build the Warming Engine: Architect cohort-based nurture journeys (including content-download, post-event, post-onboarding, and always-on nurture programs) that move contacts from first touch through consideration toward sales readiness, rather than sending high-intent accounts directly into cold sales outreach. Improve the new-user onboarding sequence, own the monthly newsletter, and manage the startup program.

  • Work at the Intersection of Data, AI, and Marketing: Use signals, scoring, AI tools, and connected workflows to identify who to target, determine the next best action, and execute campaigns efficiently. Get ahead of agent-driven discovery: make content and signals legible to the tools buyers now use to choose vendors.

  • Product Fluency and Technical Storytelling: Develop a deep understanding of our product, its technical capabilities, use cases, and competitive differentiation. Partner with Product Marketing for relevant, value-driven campaigns.

Who You Are

  • Demand Gen Experience: 3-5+ years in demand generation, growth marketing, or lifecycle marketing, running campaigns end to end in B2B tech, ideally toward technical audiences or for open-source products.

  • Lifecycle Expertise: Hands-on experience building, measuring, and optimizing cohort-based nurtures via email and in-app.

  • Builder Mindset: You're not just an operator; you build the workflows instead of relying on an existing machine, pull and shape data yourself to build lists and scoring, and you're fluent in signal and scoring tools.

  • Systems-Level Thinking: You execute the task in front of you while understanding how each campaign, workflow, and data point feeds the broader growth engine.

  • Technical Workflow Fluency: You're familiar with agentic approaches and think in connected tools and automated workflows, not manual steps.

  • Problem Solving: You work from a goal and can identify the steps and systems needed to get there.

Why Join Us

  • 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.

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Qdrant (operating under qdrant.tech, legally Qdrant Berlin GmbH) is the premier, enterprise-grade open-source vector database management system, high-performance neural search engine, and similarity matching orchestration powerhouse engineered to act as the definitive, high-velocity infrastructure layer for Retrieval-Augmented Generation (RAG), large language model (LLM) persistent memory, and multimodal AI applications. Founded in 2021 by expert distributed systems and machine learning technologists Andre Zayarni and Andrey Vasnetsov, the corporate ecosystem completely eliminates the severe performance degradation, index-rebuilding latency spikes, and structural memory erosion commonly associated with legacy relational database plug-ins and primitive K-Nearest Neighbor (KNN) wrappers by building its custom storage architecture entirely from scratch in Rust. Moving far beyond traditional keyword search methods or high-latency post-filtering mechanisms, Qdrant natively unifies expansive JSON metadata payload filtering during HNSW graph traversal, native hybrid search combining dense and sparse vectors, ColBERT-based token-level late interaction reranking, and dynamic multivector storage configurations into a single high-availability data infrastructure framework. As the primary engine trusted by global developer communities and high-scale enterprise platforms, its open-source repository commands over 29,000 GitHub stars and powers critical AI pipelines for forward-thinking organizations globally. Backed by elite international venture groups, the enterprise has secured over $87 million in institutional funding—culminating in a massive Series B capital acceleration led by Spark Capital alongside 42 Capital and AVP to scale its managed Qdrant Cloud operations and native inference engine integrations. Under the hood, its technology stack harnesses advanced vector quantization strategies (including scalar and binary quantization) to execute up to a 64x memory footprint reduction with minimal recall loss, alongside real-time data indexing capabilities that expose newly added vector points instantaneously to active queries. Headquartered in Berlin, Germany, with a globally distributed remote engineering presence, the firm operates with absolute deterministic execution correctness across multi-tenant cloud and on-premise infrastructure environments. What sets Qdrant apart is its uncompromising dedication to replacing complex, multi-stage data orchestration loops with real-time, one-stage filtered similarity traversal and deep memory optimization; by bridging the gap between high-volume programmatic data repositories and millisecond-level neural vector retrieval, the corporation remains a definitive cornerstone of modern infrastructure scaling and worldwide applied artificial intelligence transformation.

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