Senior Full-Stack Engineer - AI

• Are you an experienced Full-Stack Engineer who enjoys building secure, scalable backend solutions and integrating modern AI capabilities into enterprise applications?
• Do you thrive in collaborative environments where you can work with real-time data, cloud-native technologies, and cross-functional teams to deliver reliable, business-critical solutions?
• Ready to grow your career with a global AI and cloud leader, working on innovative technologies that make a real impact across industries and markets?

Practical Information

Location: Riyadh, Saudi Arabia | Work Arrangement: Hybrid | Reports to: Service Line Delivery Lead | Contract type: Full-time | Visa Requirements: Valid Visa for KSA | Language Requirements: Fluent/professional English, written and verbal, Arabic is a strong plus

We are looking for a Senior Full-Stack Engineer with strong expertise in backend development, systems integration, and application deployment to help build and enhance enterprise AI-enabled solutions within a secure industrial environment. In this role, you will focus on developing robust backend services and APIs, enabling real-time data integration, ensuring application reliability, and supporting containerized deployments and production readiness. The ideal candidate is comfortable working with modern web architectures, enterprise integrations, AI/ML services, and container platforms such as OpenShift and Kubernetes.

Key Responsibilities

• Design, develop, and maintain secure backend services and APIs for enterprise web applications
• Build and enhance application services for reporting, dashboards, notifications, user workflows, administrative functions, and AI-enabled capabilities
• Integrate applications with enterprise data sources, operational platforms, document repositories, notification services, and existing backend systems
• Develop and support real-time or near-real-time data flows using APIs, WebSockets, Server-Sent Events, message queues, and similar integration patterns
• Collaborate with AI and data teams to integrate model outputs, analytics services, RAG/LLM capabilities, and monitoring components into application workflows
• Support containerized deployments using Docker and OpenShift/Kubernetes, leveraging Bitbucket/Git, CI/CD pipelines, release management, environment configuration, and deployment validation
• Ensure application reliability, security, and operational readiness through troubleshooting, logging, monitoring, performance optimization, patch releases, secure coding practices, testing, documentation, and close collaboration with architects, frontend engineers, DevOps, cybersecurity teams, and business stakeholders