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Tech Manager AI at Trafilea. Location Information: Argentina. 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. This is a . builder role, not a manager role. .. You will:. Architect and scale . AI systems in production. (LLM agents, recommendation engines, personalization). Design . multi-agent workflows and AI microservices. that operate at scale. Turn business problems into . AI-driven solutions with measurable impact. Ship AI features that directly improve . conversion, retention, and customer experience. Build and lead a . high-performance AI team (2–5 hires per quarter). Establish . MLOps, CI/CD, monitoring, and scalable AI infrastructure. 5+ years leading engineering teams. in high-performance, fast-paced environments. 3+ years building and shipping AI/ML systems in production. (LLMs, recsys, personalization, or similar). Hands-on experience with . LLMs, AI APIs, and frameworks (LangChain or similar). Strong experience designing . scalable architectures, microservices, and AI pipelines. Proven track record of delivering . AI solutions tied to business impact (CVR, revenue, UX). Experience with . AWS and cloud-based AI infrastructure. Solid understanding of . MLOps (deployment, monitoring, model lifecycle, performance). Experience . hiring, mentoring, and scaling engineering teams. Strong ability to connect . technical decisions with business outcomes. Advanced English (global, remote team)