Replit

Software Engineer, Growth Infrastructure

Backend-leaning engineer building the systems behind growth experiments, analytics pipelines, and automated campaign and onboarding workflows at an AI app-creation platform.

The role

This role sits on a newly formed growth team inside an AI-driven software creation company. The engineer builds the platform layer that lets growth and product teams run experiments, collect metrics, and ship changes without heavy manual setup. Work spans backend services, data flows, and cross-team technical planning.

What you would do

  • Build and upkeep scalable services that power growth testing and experiments
  • Create and tune analytics flows that track acquisition, activation, and retention figures
  • Set up automated pipelines for onboarding sequences, campaign dispatch, and performance tracking
  • Wire experimentation frameworks into live production systems and keep them dependable
  • Automate how feature flags and growth tests get released to users
  • Work with growth PMs, data engineers, and analysts to turn business aims into system designs
  • Watch over monitoring and alerting for growth services and resolve production incidents
  • Maintain data accuracy so reporting and decisions can be trusted
  • Keep up with new tooling and push for good habits in provisioning code, delivery pipelines, and test automation
  • Coach teammates on how the growth infrastructure is built and operated

What they asked for

  • CS or software engineering degree, or a similar technical background
  • At least three years building backend or infrastructure services
  • Solid coding ability in Python, Go, or JavaScript
  • Hands-on work with a major public cloud provider
  • Working knowledge of data pipelines, ETL, and database systems
  • Practical experience with delivery automation and infrastructure-as-code tooling
  • Prior use of an experimentation platform, whether a vendor product or an internal build

Nice to have

  • Familiarity with growth metrics and product analytics software
  • Experience designing or scaling A/B testing and feature flag systems
  • Comfort with container tooling and distributed architectures
  • Exposure to observability platforms
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