Limassol, Cyprus

Role location and working style:

This is position is based in Limassol, Cyprus with an in-office and hybrid set up. Remote set up is not possible.

About e Toro:

e Toro is the platform where you can trade, invest, save, and spend. Founded in 2007 with the vision of a world where everyone can trade and invest in a simple and transparent way, we've built a regulated, Nasdaq-listed platform used by millions of people in 75 countries.

We believe there is power in shared knowledge. By combining the collective intelligence of our community with AI-powered tools, we've created a collaborative investment community designed to help you grow your knowledge and wealth.

On e Toro, you can hold a range of traditional and innovative assets and choose how you invest: trade directly, invest in a portfolio, copy other investors, or invest with an AI agent. Visit our Media Centre for the latest news.

You can find out more about eToro here.

Role Summary

We’re hiring a Biz Ops AI Developer to build** AI-powered operational systems and agentic applications** that improve efficiency, automation, and decision-making across the organization.

This is a hands-on engineering role where you will design, build, and ship production-grade AI systems - working closely with a Squad Lead, Product Managers, and business stakeholders.

You will operate at the intersection of AI engineering, full-stack development, and business operations, developing scalable AI capabilities that integrate directly into internal tools and workflows.

What will you be doing?

• Design, build, and deploy AI agents and applications end-to-end
• Develop RAG pipelines, including data ingestion, embeddings, retrieval, and LLM orchestration
• Implement agentic workflows, including tool-calling, structured outputs, and multi-step reasoning systems
• Build backend services, APIs, and integrations with internal systems (CRM, databases, third-party tools)
• Contribute to frontend/internal tools that embed AI into operational workflows
• Work with structured, unstructured, and vectorized data to support intelligent automation
• Improve system performance through evaluation, testing, and iteration
• Monitor and optimize systems for reliability, scalability, and cost efficiency
• Collaborate closely with product and business stakeholders to translate requirements into practical solutions
• Contribute to shared AI infrastructure and reusable components across teams