Senior AI Engineer

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.

Key Responsibilities

We're looking for a skilled AI Engineer to join our team and design cutting-edge software solutions for our AI-driven systems. In this role, you'll have the opportunity to innovate, propose new solutions, and work on high-impact projects that improve product quality, security, and performance. As a key member of our team, you'll work on developing, testing, and maintaining scalable and maintainable AI solutions, with a focus on large language models (LLMs) and system performance.

• Participate in designing and planning software solutions for AI-driven systems.

• Suggest and implement new solutions and improvements to existing technology systems.

• Collaborate with engineering teams (Frontend, UX, etc.) to solve technical challenges.

• Document technical solutions with diagrams and clear explanations for other technical teams.

• Advocate for improvements in product quality, security, and performance.

• Write clean, maintainable code that meets internal standards for scalability and high-performance web environments.

• Recognize and address technical debt to improve team efficiency.

• Manage LLM cost, latency, and flow traceability, utilizing Langfuse for debugging.