Product Lead, Replit

• The ideal candidate has deep channel expertise across paid search, paid social, and lifecycle, but their real edge is building AI-powered workflows that scale creative production, automate measurement, and compound institutional knowledge
• This is an IC role for someone who builds systems, not just campaigns. Someone who uses AI and automation aggressively to do what traditionally requires an entire team. You don't need an engineering background. You need the instinct to build: when you see a repetitive task, you reach for Replit or an API before you reach for a spreadsheet
• 5+ years in performance marketing across at least two major paid channels (search, social, ASO, or programmatic)
• Hands-on experience building AI-powered marketing workflows — not just prompting, but durable systems that run and improve on their own
• Deep understanding of conversion tracking, attribution, and signal quality — you know the difference between filtering conversions and excluding audiences
• Data-literate: comfortable with SQL, dashboards, and statistical rigor without needing a data team to interpret results
• Track record managing significant budgets with clear ROI accountability
• Strong experimentation instincts — structured test-and-learn programs, not one-off A/B tests

Desirable

• We're looking for an AI-native product growth lead to own Replit's entire paid acquisition and lifecycle marketing engine as the single DRI
• You'll have data science and data engineering partners for infrastructure and modeling, and brand marketing will set creative direction. Your job is to turn that direction into a closed-loop optimization system: a self-improving system that turns performance data into better creative, optimizes spend across channels in near-real-time, and compounds every insight so nothing learned is ever lost. Each cycle, the system gets smarter. That's the engine you'll build and own
• Own full-funnel performance marketing across paid search & social, ASO, and lifecycle
• Build a self-improving creative engine: AI-driven ad generation, testing, and iteration that scales without scaling headcount
• Maintain a persistent knowledge layer so every experiment, result, and creative insight compounds automatically into the next cycle
• Own conversion signal quality end-to-end: right events, right audiences, right attribution, partnering with DE on the infrastructure
• Run a structured experimentation program where every test feeds a feedback loop, not a one-off report
• Automate performance reporting and alerting — your system flags problems (creative fatigue, CAC shifts, payback drift) before anyone has to ask
• Build geo-differentiated strategies across market tiers and decompose performance by region before diagnosing aggregate shifts
• Build the system that allocates spend, prioritizes tests, and rotates under-performers — the math makes the decisions; you build and own the engine that produces them
• This is not a traditional marketing role. You'll operate more like a growth EM or PM who happens to focus on paid channels
• AI-First Execution: You automate before you do anything manually. Your primary tools are code, APIs, and AI workflows — not spreadsheets and platform UIs
• Systems Over Tasks: You build loops, not checklists. Every manual process is a candidate for automation; every insight feeds back into the system
• Strategic Partnership: You orchestrate brand, data science, and data engineering into a cohesive performance engine. Marketing feeds the system with creative direction and assets; you build the optimization loop that tests, scales winners, and returns performance insights to sharpen the next creative cycle
• Bias to Action: You ship fast, learn fast, and design experiments that generate the data you need rather than waiting for perfect information