BizOps Developer Agentic AI
eToro is a social investing platform for trading and managing stocks, ETFs, crypto and other assets.
Funding history
Projects
About eToro
eToro is a social investing platform (etoro.com) offering stocks, ETFs, crypto and other assets to retail users worldwide, with a real and long-standing crypto business (eToro Money crypto wallet).
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Design, build, and deploy AI agents and applications, develop RAG pipelines and agentic workflows, build backend services and APIs, contribute to internal tools, work with structured and vectorized data, improve performance through evaluation, monitor reliability and cost, collaborate with stakeholders, and contribute to reusable AI infrastructure.
Requirements
- 2+ years of software engineering experience
- Hands-on experience with production AI or LLM-based systems
- Experience with RAG systems, embeddings, and retrieval pipelines
- Familiarity with LangChain, LangGraph, Semantic Kernel, or similar frameworks
- Experience with tool calling, structured outputs, and workflow orchestration
- Strong backend development skills across APIs, services, and integrations
- Experience with AI-native development tools such as Cursor or Claude Code
- Familiarity with cloud environments, preferably Azure
- Understanding of scalability, reliability, and observability
- Strong problem-solving and communication skills
- Experience with multi-agent systems, LLM evaluation, vector databases, data pipelines, internal tools, or distributed systems is beneficial
Responsibilities
- 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 with tool calling, structured outputs, and multi-step reasoning
- Build backend services, APIs, and integrations with internal systems
- Contribute to frontend and internal tools embedding AI into operational workflows
- Work with structured, unstructured, and vectorized data
- Improve system performance through evaluation, testing, and iteration
- Monitor and optimize reliability, scalability, and cost efficiency
- Translate product and business stakeholder requirements into practical solutions
- Contribute to shared AI infrastructure and reusable components
Benefits
- Automate and scale operational workflows
- Improve decision-making with intelligent systems
- Enable reusable AI platforms across departments
- Drive measurable efficiency and business impact