eToro is the trading and investing platform that empowers users to invest, share, and learn. We were founded in 2007 with the vision of a world where everyone can trade and invest simply and transparently. We have created an investment platform that is built around collaboration and investor education. On our platform, users can view other investors’ portfolios and statistics, and interact with them to exchange ideas, discuss strategies, and benefit from shared knowledge. We have 40 million registered users from 75 countries, and our platform is available in 20 languages. eToro is an innovative, fast-growing business and is listed on Nasdaq in May 2025. We have over 1,500 employees across more than 10 offices around the globe, strategically positioned to serve the needs of users. You can find out more about eToro here.
Role Summary
We’re hiring a BizOps 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