Senior AI-Native Engineer

About the role

Payoneer is a global financial platform that removes friction from cross-border business. Founded in 2005, we connect underserved businesses in over 190 countries and territories to a rising global economy. Our community of more than 2,500 colleagues delivers payments, compliance, multi-currency, workforce management, working capital, and business intelligence solutions. We simplify complexity so businesses can operate worldwide with confidence. This role is within our high-impact AI Engineering team in R&D where you will own problems end-to-end, from business discovery to production monitoring. This is a new way of working at Payoneer: you will work directly with business stakeholders, ship AI-driven capabilities at speed, and help define the methodology as we build it. As part of the AI Foundations organization, you will lead best practices, champion early adoption of new technologies, and influence the direction of our R&D guild. You will build and ship current agentic applications that deliver seamless experiences to our users while ensuring robust delivery standards.

Key facts

What you'll do

Draft decision rules and risk thresholds with business partners to clarify solution intent and align on measurable outcomes.

Orchestrate agentic workflows and multi-step pipelines using AI tooling to accelerate delivery and reduce manual overhead.

Construct evaluation frameworks and test sets so every release can be measured against quality and business metrics before launch.

Establish monitoring, alerting, and observability on day one to track production behavior and surface anomalies in real time.

Shape engineering standards and tooling for the pod to guide best practices across teams and ensure consistency at scale.

Decompose complex business problems into reusable capabilities and orchestrated service flows that can be iterated upon independently.

Champion early adoption of new AI technologies and influence R&D direction for the guild by evaluating emerging tools and patterns.

Build production-ready components that turn prototypes into reliable customer-facing features with clear ownership and maintenance paths.

Partner with platforms and infrastructure teams to ensure secure, scalable deployment of AI services that meet operational requirements.

Translate compliance and regulatory needs into technical constraints for solution design so that risk is addressed from the start.

Define and track product metrics that demonstrate impact, using data to drive decisions and prioritize next improvements.

Automate repetitive tasks in the development lifecycle to free up capacity for creative problem-solving and high-value design work.

Collaborate across functions to identify opportunities where AI can enhance existing products and create new differentiated experiences.

Document decisions, trade-offs, and learnings to build institutional knowledge that accelerates future experimentation and onboarding.

Act as a technical leader who mentors peers, shares insights, and elevates the overall quality of engineering output.

Requirements

Bring 5+ years of experience building and operating production software systems in fast-moving environments where ambiguity is common.

Handle AI/ML systems in production including shipping, monitoring, and iterative improvement based on observed performance.

Use AI-powered development tools daily to accelerate delivery and reduce cycle time, leveraging them for code, testing, and documentation.

Design agentic architectures with orchestration, RAG pipelines, fallback paths, and error handling to ensure resilient solutions.

Define metrics, validate results, and set success criteria before releasing any solution to reduce risk and ensure alignment.

Move comfortably across prompt engineering, backend services, data pipelines, and infrastructure to troubleshoot issues end-to-end.

Operate independently from problem definition through production deployment without needing detailed specs, taking ownership of outcomes.

Communicate risks clearly, give direct feedback, and collaborate openly; fintech or regulated-environment experience is an advantage for navigating constraints.

Maintain a strong bias for action while balancing speed with quality, reliability, and adherence to regulatory expectations.

Demonstrate curiosity and a learning mindset, staying up to date with advances in AI techniques and applying them where they create real value.

Nice to have

Preference for contributors who have worked in regulated environments and understand compliance constraints, enabling smoother implementation of governance requirements.

Experience contributing to open source or building internal tools that improve developer productivity and collaboration.

Background in financial services or other highly regulated industries where risk management and auditability are critical.

Practical notes

This role requires availability during standard business hours as defined in the official apply page.

All hiring timelines, interview schedules, and deadlines are managed through the official apply page and must be followed precisely.

Relocation, if applicable, and visa support details are outlined solely Travel requirements, if any, are specified exclusively Skills and tools

Python, AI/ML, RAG, LLMs, MLOps, Production monitoring, Cloud infrastructure.

About the company

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