About the job
About Payoneer
Established in 2005, Payoneer serves as a global financial platform designed to streamline cross-border business, with a mission to link underrepresented businesses to the burgeoning global economy. Our diverse community consists of over 2,500 professionals worldwide, dedicated to supporting customers and partners across more than 190 countries and territories.
By simplifying complex financial workflows—including global payments, compliance, multi-currency management, workforce solutions, working capital provision, and business intelligence—we empower businesses with the necessary tools to operate efficiently and expand confidently in the global marketplace.
Role Summary
As a member of a dynamic AI Pod (3–5 engineers) within our R&D team, you will take ownership of projects from start to finish. This entails grasping business needs, architecting solutions, implementing them, and supervising production monitoring. This innovative approach at Payoneer allows you to collaborate directly with business stakeholders, deliver AI-driven capabilities rapidly, and help establish the methodology as we evolve.
Location
Hybrid - Herzliya, Israel
Full-time
What You'll Do
- Oversee the complete development cycle: identify business challenges, define solutions, architect, build, deploy, and monitor in production.
- Leverage AI as your primary development instrument, accomplishing in a single day what previously required a week for a team.
- Work alongside your AI Pod and business stakeholders to define decision logic, establish risk thresholds, and determine success metrics.
- Design and implement evaluation frameworks for every solution—only ship what you can measure.
- Manage production readiness, including monitoring, alerting, and observability from day one.
- Contribute to the evolution of team practices, tools, and engineering standards within the pod.
- Break down business challenges into actionable workflows, orchestrated processes, and reusable capabilities.
Who You Are
- 5+ years of software engineering experience, with a focus on developing and operating production systems.
- Hands-on experience with AI/ML systems in a production environment—not just prototyping, but shipping, monitoring, and iterating.
- Fluent in utilizing AI-driven development tools, leveraging them daily to enhance productivity.
- Experienced in designing agentic architectures: orchestration, multi-step workflows, RAG pipelines, fallback and error handling.
- Possess strong evaluation instincts—define metrics, create test sets, and validate solutions before deployment.
- Comfortable...

