QuantInsti - Manager - AI Driven Performance Marketing

Manager, AI Driven Performance Marketing

About the Role

This is not a traditional PPC Manager role. We're building toward a model where execution, the actual campaign setup, creative generation, reporting, and optimization, is handled substantially through AI systems and workflows rather than manual, hands on labor. What we need is someone who can direct that AI driven execution with strong strategic judgment, catch what the AI gets wrong, and continuously push the approach beyond what conventional PPC playbooks or off the shelf AI tools would produce on their own.

Key Responsibilities

- Strategy and Direction: Own the PPC and performance marketing strategy across Google Ads, Meta, and other platforms, and translate that strategy into AI workflows and prompts rather than manual execution.

- AI Orchestrated Execution: Set up, manage, and continuously refine AI systems and workflows (using tools like Claude, MCPs, and similar) to handle campaign setup, creative generation, audience building, and reporting.

- Quality Control and Judgment: Review AI generated campaigns, creative, and recommendations critically. Know when to trust the output and when to override it, this is a core skill the role depends on.

- Innovation Beyond the Default: Go beyond what AI tools suggest out of the box. Use data science thinking to identify original hypotheses and approaches that conventional PPC tactics or default AI recommendations would miss.

- Data Science Driven Optimization: Use data analysis (Python, SQL, or similar) to identify patterns in performance and lead quality data that go beyond what AI tools or dashboards surface on their own.

- Experimentation: Design and run structured experiments (audience hypotheses, creative approaches, bidding strategies, attribution models), with AI handling much of the execution and you handling the hypothesis design and evaluation.

- Budget and Lead Quality Ownership: Manage budgets toward ROAS targets, with real attention to lead quality rather than just CPL or CTR.

- Attribution Thinking: Work comfortably with attribution models beyond last click or short window defaults.

- Cross Functional Collaboration: Partner with SEO, creative, product, and analytics teams, and clearly explain AI driven decisions and unconventional approaches to stakeholders who may be more used to traditional metrics.