• Be a technical point of contact for various stakeholders • Be hands-on in both coding and architecture • Partner closely with Engineering and Product leadership to shape roadmaps • Mobilise the team around high-impact problems • Lead and influence architectural direction for the most complex systems • Set and uphold a high bar for technical excellence across the team • Proactively mentor, sponsor and develop senior engineers • Champion the adoption of AI-assisted development practices and tools

• Build, evolve, and run production services and UI capabilities in a Self-Contained Systems environment with end-to-end team ownership. • Deliver backend solutions using Java/Kotlin + Spring Boot, developing reliable microservices and robust REST APIs. • Deliver frontend capabilities by consuming and extending Web Components / design system components, building Vue-based client-side rendered (CSR) experiences and contributing to server-side rendered (SSR) / MVC templates when required. • Implement event-driven integrations using Kafka (Streams highly valued), alongside synchronous HTTP integrations where needed. • Apply Domain-Driven Design (DDD) and hexagonal / ports-and-adapters architecture to model and evolve complex retail domains. • Engineer for resilience and reliability using patterns like timeouts, retries, bulkheads, and fallbacks, and ensure services are observable in production. • Take shared ownership of quality across the SDLC (unit, integration, and E2E testing) with no separate QA department. • Work in an XP/Agile way (pairing/mobbing, continuous refactoring, frequent releases) and support a culture of learning and knowledge-sharing. • Operate with a “you build it, you run it” mindset: collaborate on CI/CD, monitoring, incident response, and continuous improvement.

Role Description Join IntelliSense.io and help build the future of Scientific Intelligence. As a Backend Engineer, you'll design and implement robust data solutions that meet both internal and client needs. You'll also play a key role in shaping how we build software, setting standards, and helping teams deliver high-quality work. - Extracting requirements, designing, developing, and testing software applications - Liaising with different teams, including QA team and data scientists to ensure the best processes are used to create the best outcome of a product - Troubleshooting and resolving issues related to applications and services - Identifying bugs in the microservices and proposing solutions to fix them - Collaborating with the data science team to integrate equipment/process models into software components and services - Applying principles, best practices, and techniques of engineering, mathematics, and computer science to software development - Defining and implementing Unit Test codes, and providing test coverage for the developed software components or services - Writing and maintaining documentation for all services and their dependencies Qualifications - Experience in software engineering, with a strong focus on data systems - Proficiency in Java and Node.js - SQL skills and experience with both relational and NoSQL databases - Hands-on experience with message queues (e.g. NATS, Pub/Sub) - Experience building web services using REST and SOAP - Working knowledge of Kubernetes and Docker - Excellent communication skills and confidence working in distributed teams - A degree in Computer Science (or a related field), or equivalent practical experience - Fluency in English and Arabic languages Benefits - Opportunity to work on cutting-edge technology and meaningful data challenges - A collaborative, global team of talented engineers and domain experts - A continuous learning environment with real opportunities to grow and lead Location This role is remote but must be based in Saudi Arabia. We actively encourage applications from people of all backgrounds. If this role excites you, even if you don't meet every requirement, we'd love to hear from you. You belong here. Let's build something extraordinary together.

• Diseñar, desarrollar e implementar soluciones de Inteligencia Artificial y Machine Learning. • Construir y gestionar plataformas de datos y flujos de trabajo de IA sobre Google Cloud Platform (GCP). • Desarrollar arquitecturas basadas en Agentic AI utilizando Vertex AI y Gemini Enterprise. • Desplegar y administrar aplicaciones en entornos Kubernetes (GKE). • Automatizar infraestructuras mediante Terraform (Infrastructure as Code). • Implementar y mantener pipelines CI/CD, DevOps y MLOps. • Optimizar el rendimiento, la escalabilidad y la fiabilidad de las soluciones de IA. • Colaborar con equipos multidisciplinares para transformar necesidades de negocio en soluciones de producción. • Documentar soluciones y contribuir a la mejora continua de las plataformas.