we are looking for a AI-Native Pod Leader.
The AI-Native Team Leader is a new kind of engineering leader at Payoneer - equal parts technical authority, people developer, and AI-first builder. Youll 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 youll 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 wont inherit a playbook, youll write it
Requirements: 5+ years as a backend or full-stack engineer with real production experience - youve watched systems run in the real world and fixed what breaks
2+ years leading engineering teams - youve 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 dont 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 youre wrong, you update and move on
This position is open to all candidates.