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Cursor Developer / AI-Driven Development Specialist

Trafilea · Remote

Software DevelopmentRemoteQuick applyfull-time2 days ago

About The Role

About Trafilea

Trafilea is a Consumer Tech Platform for Transformative Brand Growth. We’re building the AI Growth Engine that powers the next generation of consumer brands.

With over $1B+ in cumulative revenue, 12M+ customers, and 500+ talents across 19 countries, we combine technology, growth marketing, and operational excellence to scale purpose-driven, digitally native brands.

We own and operate our own digitally native brands (not an agency), with presence in Walmart, Nordstrom, and Amazon, and a strong global D2C footprint.

Why Trafilea

  • We’re a tech-led eCommerce group scaling our own globally loved DTC brands, while helping ambitious talent grow just as fast.
  • 🚀 We build and scale our own brands.
  • 🦾 We invest in AI and automation like few others in eCom.
  • 📈 We test fast, grow fast, and help you do the same.
  • 🤝 Be part of a dynamic, diverse, and talented global team.
  • 🌍 100% Remote, USD competitive salary, paid time off, and more.

Job Responsibilities

Your mission: transform Cursor from a smart assistant into a genuine engineering multiplier — someone who uses AI to accelerate excellence, not to replace craftsmanship. You’ll ensure every line of AI-generated code meets professional standards in architecture, performance, and security.

  • Design, build, and optimize AI-assisted development workflows by integrating Cursor (or equivalent tools) into the team’s codebase, CI/CD, and automated testing pipelines.
  • Create and maintain prompt libraries, templates, macros, and recipes to standardize and scale recurring engineering tasks.
  • Audit, refine, and validate AI-generated code for quality, coherence, maintainability, and security compliance.
  • Train and mentor other developers on how to leverage Cursor effectively as part of their daily workflow.
  • Act as a bridge between product, architecture, and engineering, ensuring that AI-generated output aligns with the system’s overall design principles.
  • Define and monitor key performance metrics such as code quality, time saved, and refactor success rate.
  • Stay at the frontier of LLM and AI code generation advancements, recommending new tools and automation strategies to continuously raise the bar.

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