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Payoneer, founded in 2005, is a global financial platform serving over 2,500 colleagues and customers in 190+ countries. The company simplifies cross-border business by removing friction from financial workflows—payments, compliance, multi-currency management, workforce solutions, and business intelligence.
You will join a high-impact AI engineering team within R&D, owning problems end-to-end: understanding business needs, architecting solutions, implementing them, and monitoring production. This represents a new way of working at Payoneer—you'll work directly with business stakeholders, ship AI-driven capabilities at speed, and help define methodology as the organization builds it.
As a member of the AI Foundations organization, you will lead best practices, champion early adoption of new technologies, and influence the direction of the R&D guild by building and shipping cutting-edge agentic applications.
Key responsibilities:
- Own the full development loop: understand the business problem, define the solution, architect, build, ship, and monitor in production
- Use AI as your primary development tool to accelerate delivery
- Collaborate with team and business stakeholders to define decision logic, risk thresholds, and success metrics
- Design and build evaluation frameworks for every solution
- Own production readiness: monitoring, alerting, and observability from day one
- Contribute to shaping team practices, tooling, and engineering standards
- Decompose business problems into agentic workflows and reusable capabilities
Required qualifications:
- 5+ years of software engineering experience building and operating production systems
- Strong hands-on Node.js + TypeScript experience, preferably with NestJS
- Strong fundamentals: REST APIs, async patterns, debugging, performance optimization
- Experience with SQL and NoSQL data sources
- Distributed systems knowledge: Redis, Kafka/RabbitMQ, containers, Kubernetes
- Strong CI/CD, feature flags, and environment management expertise
- Daily fluency with AI-powered development tools
- Strong evaluation instincts and metrics-driven approach
- Full-stack comfort moving between backend services, data pipelines, and infrastructure
- High independence and ability to lead work from problem definition to production
- Excellent communication and risk flagging
- Fast learning ability and comfort with ambiguity
Nice-to-have:
- Production AI/ML systems experience (shipping, monitoring, iteration)
- Agentic architecture design (orchestration, multi-step workflows, RAG, error handling)
- LLM/agent experience (OpenAI, LangChain, function calling)
- Observability tools (Langfuse, OpenTelemetry, Grafana, Datadog)
- Fintech or regulated-environment experience
