Full-stack Growth Engineer

Slate

1d•$95,000 - $200,000•Remote

About The Position

Slate is hiring its first Full-stack Growth Engineer to build and own the self-serve product-led growth (PLG) surface end-to-end. This role is crucial for expanding Slate's reach beyond specialists to a broader user base and establishing a self-serve growth engine. The engineer will be responsible for the entire self-serve funnel, from sign-up and the first-run experience to the path to paid conversion, and will establish the experimentation discipline to guide future product development. This is a highly cross-functional role, requiring expertise in full-stack development, product management, data engineering, and experimental design. The engineer will be the in-house expert for growth engineering practices within the company.

Requirements

5+ years of experience building production systems with a specialization in growth and experimentation.
Proficiency in TypeScript/Node.js and a modern frontend framework.
Deep familiarity with experimentation concepts: controls, test groups, statistical significance, guardrails, anti-goals, exposure logging, and longitudinal measurement.
Strong product analytics skills (experience with Amplitude, Mixpanel, Segment, Statsig, LaunchDarkly, or similar).
Clear understanding of how to wire up the analytics and experimentation stack.
Proven experience building or owning a PLG funnel end-to-end (sign-up, activation, conversion, payment) at a company where PLG is a core discipline.
Experience from a company with a mature experimentation culture where it's a first-class engineering practice.
Experience designing experiments with proper controls, running them to statistical significance, and making data-driven decisions to ship, iterate, or kill features.
Commitment to balancing data-driven insights with user experience ('soul' and 'statistics').
Ability to own outcomes, not just tasks.
Capacity to move from strategy to implementation within the same week.
Proficiency in using AI tools in personal workflow and taking responsibility for their output.
Clear communication skills, proactive issue raising, and the ability to ship without constant permission.

Nice To Haves

Hands-on experience with Stripe, billing, and recurring payments.
Experience integrating billing and managing its operational aspects (trials, upgrades, downgrades, dunning, tax, refunds).

Responsibilities

Build the self-serve surface, end-to-end.
Design and ship a self-serve sign-up and payment flow, converting anonymous visitors to paid users without sales interaction.
Define and instrument trial limits (e.g., AI credit budgets, storage caps, seat counts) to balance user wow-factor with upgrade incentives.
Surface high-intent upsell signals to the sales team to ensure PLG and enterprise efforts complement each other.
Integrate billing systems (Stripe/recurring payments) and manage associated operations like trials, upgrades, downgrades, dunning, tax, and refunds.
Address the 'cold start' problem by making Slate approachable from the first minute of use.
Own the new-user journey, guiding users from sign-up to creating their first piece of branded content quickly to prevent churn.
Apply the hook model (Trigger, Action, Variable Reward, Investment) to all stages of the activation surface.
Influence product changes to make Slate usable by non-specialists.
Collaborate with the AI team to develop innovative technology enabling new users to see their brand within the product rapidly.
Establish and maintain a robust experimentation discipline.
Set up the experimentation platform, including event tracking, attribution, cohort analysis, and exposure logging.
Conduct experiments with proper controls, test groups, statistical significance, and pre-registered guardrails/anti-goals.
Measure both short-term conversion metrics and long-term business outcomes (retention, paid plan uptake, expansion, LTV) using longitudinal measurement.
Treat product changes as hypotheses, designing, running, and evaluating them based on data to decide whether to ship, iterate, or kill.
Act as the in-house growth engineering expert, elevating experimentation standards across the entire engineering team.