Growth Engineer, Product Growth
About the company
Our client is a fast-growing developer-infrastructure startup whose APIs turn messy web content into clean, structured data that AI teams build on. They went from nothing to eight figures of ARR in their first year and more than doubled it in the second, on a Series A and a team of 39. It is a remote-first company with a San Francisco hub, and the engineering culture is deliberately flat — no committees, no approval chains, ship on Monday and see it in production by Friday.
The role
This is a full-stack engineering seat pointed entirely at growth. You would own the signup, activation, onboarding and conversion experience, and you would be measured on the funnel metrics you move rather than the features you ship. The expectation is scientific: form a hypothesis, instrument it, run the experiment, read the result honestly and iterate. You own a number from day one, and the developer-facing surfaces you build are the first thing a new user touches.
What you'll do
- Own the growth surfaces end to end — signup, activation, onboarding and conversion
- Instrument the funnel, run real experiments, and ship the changes that move the metric
- Build full-stack, from the first screen a developer touches to the backend powering it
- Treat conversion and activation as your number — own it, measure it, move it
- Work close to the data: hypothesis, test, iterate fast on what actually works
What we're looking for
These are hard requirements. Check each one that applies to you.
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Submit Your InfoNice to have
- In-product growth surfaces shipped at a dev-tools or SaaS company — onboarding, activation, upgrade flows, in-product guidance
- Developer-facing product work: SDKs, playgrounds, docs surfaces, APIs
- Building with LLMs in production — prompt engineering, tool use, inference pipelines
- Stack fit with Next.js, Tailwind and Vercel
Tech stack
TypeScript, Node.js and React, with Next.js, Tailwind CSS and Vercel on the front end, PostgreSQL and Redis behind it, and LLM APIs, prompt engineering and inference pipelines on the AI side.
Compensation & logistics
- $190k–$265k base + competitive equity
- San Francisco / Bay Area preferred, or remote within Americas timezones (UTC-3 to UTC-10)
- Not open to any visas — candidates must already be legally authorised to work in the United States; the client cannot sponsor, transfers included
- Full medical, dental and vision at 100% employee coverage, $100/month wellness stipend, $1,000/year learning budget
- 15 days mandatory PTO, 12 weeks paid parental leave, and a 3-month sabbatical after 4 years
- 1–2 hires planned