Responsibilities

• Build AI-driven systems and automations that power the marketing engine
• Work with LLMs and first-party data to turn customer insight into marketing action
• Automate workflows across ad platforms, analytics and internal tools
• Turn insights into hypotheses, experiments and measurable outcomes
• Act as the bridge between marketing and engineering
• Explore emerging AI tooling and apply it where it moves real KPIs

Requirements

• An engineer who has sat close to performance advertising: you know what ROAS, incrementality, attribution windows and creative fatigue mean in practice, not from a blog post
• Strong with Python or Node, APIs, and cloud data warehouses (BigQuery or similar)
• You've shipped LLM systems in production, including evals, not just prompts in a playground
• You can explain pixel vs CAPI deduplication without looking it up, and you'd know how to approach automating creative fatigue detection (we will ask you both)
• You measure everything you build against revenue, not activity
• Senior mindset, high initiative; comfortable with ambiguity and owning a system where the spec is high level objectives
• Curious, experimental, analytical; you ask sharp questions and design experiments to answer them