Responsibilities

• Own the full funnel
• Take plays from spec to live: audience, signal, message, channel, landing page, conversion. You get support on strategy and full ownership of execution.
• Run experiments like they matter
• Define the metric, the guardrail, and the sample size before anything ships, not after the data looks interesting.
• Do your own analysis: cohort curves, funnel step conversion, segment cuts, time-to-activation, cost per activated account, cost per SQA. SQL against the warehouse, not a screenshot of a dashboard.
• Know the difference between a real lift and noise, and say so out loud, even when it's your own play that lost.
• Build with agents, not just tools
• Build agent workflows daily: research, list building, lookalike testing, personalization, creative variants, landing page drafts, competitor monitoring, post-test analysis.
• Point agents at our stack (Clay, HubSpot, Apollo, our marketing MCP) so plays run with you supervising, not clicking through every step.
• Prototype fast and for real: a scraper, a scoring pass, a signal listener, a one-off page, instead of scoping it out to someone else.

Requirements

• Hands-on experience with Claude Code or similar LLM tooling. This isn't a "used ChatGPT once" bar, we mean you actually build with agents.
• A resume with real quantitative results: pipeline contribution, PLG or SLG conversion metrics, cost per activated account/SQA, that kind of thing.
• Cross-channel growth experience with genuine technical chops (comfortable in SQL, can run your own cohort analysis and basic stats on test results).
• Background at a high-growth company (data/AI space preferred, but a Ramp-equivalent is fine too).
• 1-3 years in growth, performance marketing, demand gen, or a scrappy generalist marketing role, or a track record of building growth things on your own that speaks for itself.
• Great writing, and credibility with a developer and data audience.
• A bias toward shipping. If you see something no one owns, that's an opening, not a blocker.