Growth Engineer

Expo

$110K — $130K *
US-AnywhereRemote in United States
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3-5 years of software engineering experience, focusing on growth or product-led initiatives
  • Proficient in JavaScript/TypeScript and modern frontend frameworks (React preferred)
  • Full-stack skills, from frontend to backend to data pipelines
  • Experience with designing and analyzing A/B experiments
  • Familiar with product analytics tools and SQL for data analysis
  • Strong product intuition for rapid versus durable solutions
  • Excellent communication skills for remote collaboration

Responsibilities

  • Design, implement, and analyze A/B experiments to enhance conversion and retention
  • Build and iterate on growth features, such as referral systems and in-product nudges
  • Own and instrument product analytics to understand user behavior
  • Collaborate with Product, Marketing, and Data teams on growth initiatives
  • Develop growth infrastructure including experiment frameworks and segmentation
  • Investigate user churn and pain points to deliver impactful solutions
  • Guide understanding of user journeys from project creation to subscription

Benefits

  • High-autonomy role with deep ownership
  • Direct impact on core product metrics
  • Opportunity to work cross-functionally with diverse teams
  • Work in a remote environment
  • Engage with a product-led growth model that drives meaningful results
Full Job Description
We're looking for a Growth Engineer to accelerate our product-led growth flywheel across activation, retention, and monetization. You'll work at the intersection of engineering, data, and product-owning end-to-end experiments and features that directly impact our core metrics. This is a high-autonomy role with a tight build-measure-learn loop, deep ownership, and direct impact on how developers discover and adopt Expo.

What you will do

  • Design, implement, and analyze A/B experiments across sign-up, activation, onboarding, and upgrade funnels to improve conversion and retention
  • Build and iterate on growth features-referral systems, in-product nudges, email sequences, and pricing page optimizations
  • Instrument and own product analytics to deeply understand user behavior, identify drop-off points, and surface growth opportunities
  • Collaborate cross-functionally with Product, Marketing, and Data teams to drive acquisition, activation, and monetization initiatives
  • Build growth infrastructure-experiment frameworks, feature flagging, segmentation, and attribution systems
  • Investigate causes of user churn and pain points, then ship solutions that measurably improve the developer experience
  • Drive understanding of our core user journeys-from first project creation through paid subscription and expansion

Requirements

  • 3-5 years of software engineering experience, with at least 1-2 years focused on growth, experimentation, or product-led initiatives
  • Strong proficiency in JavaScript/TypeScript and experience with modern frontend frameworks (React preferred)
  • Full-stack capabilities-comfortable working across the stack from frontend to backend to data pipelines
  • Data-driven mindset with experience designing experiments, analyzing results, and making decisions based on metrics
  • Experience with product analytics tools (Rudderstack, Looker, DBT, or similar) and SQL for data analysis
  • Strong product intuition and ability to balance shipping quickly with building durable solutions
  • Excellent communication skills and ability to work autonomously in a remote environment

Nice to have

  • Experience with React Native or mobile development
  • PLG experience in developer tools, devops, or infrastructure products
  • Experience building and operating experimentation frameworks
  • Background in a high-growth startup environment
  • Experience with email marketing automation and lifecycle marketing tools (HubSpot, Customer.io, etc.)
  • Familiarity with SaaS metrics-MRR, NDR, cohort retention, LTV/CAC

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