PayPal Sr Backend Engineer AI & Platform 

Singapore, Singapore 

324893477

We are seeking a highly experienced Senior Backend Engineer with 10+ years of experience in backend systems architecture, distributed computing, and AI integration. The ideal candidate will bring deep expertise in backend engineering and machine learning, along with strong industry experience in building scalable, secure, and intelligent systems.
This role blends technical leadership, system design, and AI integration to deliver high-performance backend services that power modern, intelligent applications.

Job Description:

Key Responsibilities

• Backend Architecture: Design, build, and optimize scalable and resilient backend systems using modern cloud-native technologies.
• AI Integration: Work closely with ML engineers to integrate AI models into backend services, enabling smart, adaptive experiences.
• API & Service Design: Develop robust RESTful and GraphQL APIs and microservices to support web and mobile clients.
• Performance & Reliability: Ensure systems are highly available, secure, and performant through monitoring, load testing, and optimization.
• Data Engineering & ML Ops: Build efficient data pipelines, support model training/inference workflows, and deploy ML models in production.
• Security & Compliance: Implement best practices around authentication, data protection, and secure architecture design.
• Cross-Functional Collaboration: Partner with product, frontend, DevOps, and data teams to align engineering efforts with business strategy.
• Mentorship & Leadership: Mentor junior engineers, lead code reviews, and champion engineering best practices.
• Tech Strategy & Innovation: Stay up-to-date with industry trends in backend infrastructure, AI/ML, and cloud services; advocate for technology adoption and innovation.

Required Skills & Experience

• 10+ years of backend engineering experience in large-scale systems
• Proficiency in Node.js, Python, Java, or Go, with strong system design and debugging skills
• Experience deploying and scaling systems on AWS, GCP, or Azure
• Hands-on experience with AI/ML model integration, including inference pipelines and model lifecycle management
• Deep understanding of API design, microservices, and event-driven architectures
• Strong knowledge of SQL and NoSQL databases, message queues, and distributed data systems
• Familiarity with CI/CD, containerization (Docker), and orchestration tools (Kubernetes)
• Experience with monitoring tools like Datadog, Prometheus, or OpenTelemetry
• Knowledge of security best practices, data privacy, and compliance (e.g., GDPR)
• Excellent communication and collaboration skills in agile teams

Preferred Qualifications

• Experience with ML Ops tools (e.g., MLflow, Kubeflow, Vertex AI)
• Background in deep learning frameworks (e.g., TensorFlow, PyTorch)
• Exposure to vector databases , LLM integration , or retrieval-augmented generation (RAG) pipelines
• Experience building recommendation systems , chatbots , or predictive services
• Knowledge of backend observability , circuit breaking , and self-healing systems
• Understanding of data governance , feature stores , and stream processing

Our Benefits:

Any general requests for consideration of your skills, please