Founding GTM Engineer

🎯 Role

As Memorang's first GTM Engineer, you'll straddle engineering and growth: 50% hands-on building, 50% strategy, experimentation, and monetization. You'll architect revenue engines and optimization systems that power our entire customer base—from Fortune 500 publishers to early-stage startups.

This is a strategic, founding role at the intersection of product, data, and business.

🛠️ Sample projects could include…

• Building a new paywall experiment framework with feature flags and event tracking, enabling the team to ship 3 pricing tests per week.

• Simplifying the subscription upgrade funnel through a deep UX audit, identifying 5 friction points and shipping fixes that lift conversion by 20%.

• Designing the mobile onboarding flow in React Native, running a multivariate test that improves Day 7 retention by 15%.

• Improving lead scoring and email nurture workflows using n8n and Mixpanel, reducing manual work by 10 hours/week.

• Driving an AI-native marketplace from concept to live beta in 2 weeks, where creators can sell learning modules.

• Partnering with Product and Sales to create a live revenue dashboard that tracks activation, retention, and LTV by cohort, becoming the source of truth for growth decisions.

🤝 You might be a fit if you…

• Have 4+ years building mobile apps with direct ownership of growth or monetization funnels.

• Are fluent in React Native (Expo) with deep experience integrating Stripe and RevenueCat.

• Are proficient with analytics and CDP tools (Mixpanel, Segment, Amplitude).

• Have a proven track record running experiments that materially improved activation, retention, or revenue.

• Have solid SQL skills and are comfortable building automated funnels and performance metrics.

• Have strong UX intuition and can translate user journeys into dev-ready feature specs.

• Are written-first and async—you document decisions thoroughly.

• Are ruthlessly data-driven yet creative in testing novel business models.

• Are confident presenting to C-suite executives, internal and external.

• Thrive in ambiguity and can ship prototypes in hours, not weeks.

• Share experiment learnings proactively and update Linear issues same-day with status and evidence.