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The New York Times

Software Engineer, Growth Conversion

New York, NYFrom $130kfull-timemidAdded 3 days ago

About this role

The New York Times seeks a Full Stack Software Engineer to build and optimize subscription conversion features across web and mobile platforms. You'll work on React/TypeScript frontends and Node.js/Go backends to drive measurable business impact on NYT's subscription growth mission.

What you'll do

  • Build and optimize conversion funnels for NYT subscription customers across multiple platforms
  • Develop payment workflows for digital and print subscriptions
  • Collaborate with design, data, and marketing teams to measure business impact
  • Participate in A/B testing, design reviews, and code reviews
  • Support systems through on-call rotation responsibilities
  • Partner cross-functionally to ship end-to-end features from concept to production

What they're looking for

  • React and TypeScript
  • Node.js backend development
  • Go-based APIs
  • Git version control
  • Full-stack web application development
  • A/B testing and experimentation
  • AWS cloud platform
  • Cross-functional collaboration

Benefits

  • Medical, dental, and vision insurance
  • 401(k) company match
  • Paid vacation and sick days
  • Paid parental leave
  • Tuition reimbursement
  • Professional development opportunities
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The New York Times

The New York Times builds digital platforms and products that deliver journalism through web, mobile, and multimedia experiences, supported by modern backend systems and AI-enhanced tools. The company is hiring software engineers, QA engineers, and full-stack developers to work across content management, audio/video features, AI-driven reader experiences, and internal developer tooling.

View all jobs at The New York Times

Likely interview questions

  • Walk us through a user-facing feature you built from concept to production—how did you measure its impact?
  • Describe your experience working with A/B testing or experimentation platforms and how you've used data to inform feature decisions.