Tech Manager AI

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

Requirements

• 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)

Originally posted on Himalayas