AI-Native Pod Leader

About Payoneer

Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories.

By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence.

Role Summary

Location: Herzliya, Tel Aviv District, Israel

Hybrid / Full-time

The AI-Native Team Leader is a new kind of engineering leader at Payoneer — equal parts technical authority, people developer, and AI-first builder. You’ll lead a small AI Pod that owns its problems end-to-end: from understanding the business need, through architecture and implementation, to production monitoring. There are no hand-offs, no tickets, no specs thrown over a wall. Your team builds with AI as a primary tool, ships fast, and sets the methodology for how R&D works next.

What You’ll Do

• Lead and develop a small 3-4 engineers AI Pod, with a clear focus on their technical growth, autonomy, and delivery outcomes
• Provide technical authority hands-on — code, architect, review, and ship alongside your team
• Own the full delivery loop: understand the business problem, define the solution, architect it, ship it, monitor it — no one hands you a spec
• Collaborate directly with Product, Design/UX, DevOps, and business stakeholders to define decision logic, risk thresholds, and success metrics — building capabilities, not features
• Drive AI-native development — Claude Code, Cursor, and whatever tools give your team the most leverage; build in a day what used to take a team a week
• Build the harness before you ship — evaluation frameworks, monitoring, and observability go in on day one, not after the first incident
• Be accountable for overall design, architecture, code quality, and production environment across your team
• Set a higher technical bar — run design reviews, champion engineering best practices, and push for continuous improvement in code quality and team craft
• Define the methodology — this is early-stage work within Payoneer; you won’t inherit a playbook, you’ll write it
  
  

• 5+ years as a backend or full-stack engineer with real production experience — you’ve watched systems run in the real world and fixed what breaks
• 2+ years leading engineering teams — you’ve grown people, driven delivery, and you know the difference between managing and developing engineers
• Experience shipping production AI systems — agentic architectures, orchestration, multi-step workflows, fallback and error logic; you think in workflows, not endpoints
• Real fluency with AI coding tools — not “familiar with,” genuinely fast with them
• Strong eval instincts — you define metrics, build test sets, and don’t ship until you can measure; evaluation frameworks are part of the architecture, not an afterthought
• Full-stack comfort — you move from the prompt to the RAG pipeline to the orchestrator to the backend and back; you go where the right solution is
• Experienced and passionate about managing and growing people — strong opinions, held loosely; you make space for different perspectives and help the people around you grow
• Honest communicator — you flag problems early, give direct feedback, and say what you actually think; experienced with engineering best practices (code reviews, testing coverage, agile methodologies)
• Grounded confidence — you trust your abilities, move forward with incomplete information, make a call, and own it; when you’re wrong, you update and move on
  
  

• Fintech or regulated-environment experience — what matters is understanding why “probably fine” isn’t acceptable when money is moving
• Experience with messaging systems such as Kafka, RabbitMQ, or SQS
• Experience building SaaS platforms in a cloud-based, microservices environment
• Experience with frontend technologies such as React or Angular