Fractional Paid Media Specialist

Role Description

We are looking for a Fractional Paid Media Specialist who will help us run and optimize our paid acquisition programs. This role is focused on enterprise demand capture as well as developer/user acquisition for Qdrant, the leading open-source vector search engine used to power AI search, retrieval, and RAG systems. You will work closely with our Growth team to manage campaigns and scale high-intent acquisition channels. This is a fractional role for an experienced operator who can execute independently, as well as focus on performance and faster iteration.

What you will own

• AI-Powered Optimization
  • Use AI tools and no-code/low-code agents to automate repetitive tasks, such as bid adjustments, budget pacing, anomaly detection, search term mining, and performance reporting.
  • Build lightweight workflows that reduce manual work and surface insights faster.
  • Leverage LLMs for creative testing, keyword research, audience research, and competitive analysis.
  • Continuously look for where AI creates leverage in the campaign workflow and own the implementation.
• Own PPC Strategy & Execution
  • Manage and optimize PPC campaigns end-to-end, from account structure and keyword strategy through bidding, budget allocation, and ongoing iteration.
  • Design and launch ad creative testing plans; optimize landing pages for performance.
  • Build forecasts and scenario projections to guide decisions.
  • Ensure accounts remain on budget while balancing efficiency and growth targets.
• Google Search
  • Own strategy and execution for Google Search campaigns.
  • Optimize campaigns around high-intent technical keywords.
  • Refine keyword targeting to prioritize commercial intent and developer workloads.
  • Improve account structure.
  • Optimize bidding strategies.
  • Continuously test ad copy and landing pages to improve account creation conversions.
• LinkedIn
  • Manage and optimize conversion-focused LinkedIn campaigns targeting enterprise buyers and technical decision-makers.
  • Test audience segmentation, creative formats, and messaging to improve pipeline quality.
• Reddit
  • Run experiments targeting technical audiences for developer acquisition and competitor displacement.
  • Identify subreddits, formats, and messaging that resonate with the AI/ML infrastructure community.
  • Across all channels, test audience segmentation, creative formats, and messaging to improve pipeline quality.

Qualifications

• 3+ years running performance marketing campaigns.
• Deep expertise with Google Ads Search campaigns.
• Experience running campaigns for developer, SaaS, or infrastructure products.
• Strong command of keyword strategy, conversion tracking, attribution, and performance optimization.
• Experience with AI tooling around search and campaign optimization.

Requirements

• Nice to have:
  • Experience advertising to engineers or developer audiences.
  • Familiarity with AI / ML infrastructure tools.
  • Experience working with GA4, GTM, Segment, or server-side conversion tracking.
  • Comfortable writing prompts and light code/scripts to automate campaign operations.
  • Familiarity with no-code automation tools.
  • Experience using LLMs to accelerate keyword research, ad copy testing, or reporting workflows.

Benefits

• 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 candidates, a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy.

Company 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.