ONE ZERO is Israel’s fully digital, branchless private bank, built to deliver private‑banking–level service to a wider audience through advanced technology, automation, and AI.

As part of this mission, the bank is developing Ella, a GenAI banking copilot embedded directly into ONE ZERO’s product flows and core systems. Ella provides 24/7 multilingual support and daily financial check‑ups that detect anomalies, duplicate charges, and savings opportunities.

Behind the scenes, Ella runs on an agentic, graph‑based workflow with intent routing, retrieval and verification layers, and typed tools that can safely query live banking data and trigger in‑app actions.

Why join?

A rare opportunity to build and ship real, high‑impact AI at scale in a highly regulated environment—tackling meaningful challenges in safety, reliability, and real‑world financial edge cases.

Your Day-to-Day

• Build multi-agents and integrate them into product flows.
• Add evals, monitoring, and safety mitigations
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Optimize and fine-tune Generative Agents for performance and scalability.
• Stay up-to-date with the latest industry trends and advancements in Generative AI Industry.
• Optimize inference performance, including latency, resource usage, and throughput, while maintaining model quality.

Requirements

• B.Sc/ M.Sc. degree in Computer Science, Software Engineering, or a related technical field - a must.
• AI-native development mindset: ability to use AI across the full software lifecycle (planning/design, implementation, testing, refactoring, maintenance) while keeping high standards for architecture, quality, security, scalability, and reliability.
• Proficiency in Python and LLMs- a must.
• 3+ years of hands-on experience integrating GenAI/LLM capabilities into production applications, including strong prompt engineering and prompt optimization techniques - a must.
• Experience developing NLP models at scale, from inception to production, with business impact.
• Experience with building multi-agents with GenAI libraries and tools, such as LangChain, LangGraph, and Multi-Agent systems.
• Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
• Skill set includes software engineering, data infrastructure, and familiarity with RDBMS/NoSQL.
• Strong problem-solving skills with the ability to translate business requirements into scalable technical solutions.
• Exhibit robust problem-solving skills, with the capability to identify business challenges, formulate data-driven hypotheses, and design experiments to test and validate these hypotheses.

Advantages

• Experience building real-time, high-throughput AI applications at scale.
• Classic ML/NLP background, including deploying models at scale.