AI Software & Platform Architect

AI Software & Platform Architect – Dubai Discover the Opportunity: We're partnering with an innovative AI technology company that is building next-generation intelligent software platforms for enterprise customers. As the business continues to scale, they're looking for a Software & Platform Architect to bridge modern software engineering with cloud infrastructure, ensuring AI-powered applications are delivered through secure, scalable, and highly available platforms. This is a highly hands-on role combining software architecture, cloud-native engineering, and platform design. You'll work closely with AI, product, and engineering teams to build production-grade systems that support the delivery of cutting-edge AI applications. Discover the Responsibilities: • Design, build, and maintain scalable software applications and cloud-native platforms that support AI-powered products • Partner with AI and engineering teams to integrate machine learning models into production applications, ensuring performance, reliability, and maintainability • Design cloud architectures across AWS, Azure, GCP, or hybrid environments, with a strong focus on scalability, resilience, and automation • Lead architectural decisions around Kubernetes, microservices, Infrastructure-as-Code, CI/CD, and modern deployment strategies • Implement observability, monitoring, logging, and performance optimisation to ensure highly available production systems • Drive engineering best practices across software architecture, security, automation, and platform reliability • Collaborate with cross-functional stakeholders to translate business requirements into scalable technical solutions Discover the Requirements: • 5+ years of experience designing and delivering cloud-native software platforms and distributed systems in production environments • Strong software engineering background using languages such as Python, Go, or similar, alongside experience building scalable backend services • Deep experience with AWS, Azure, or GCP, Kubernetes, containerisation, Infrastructure-as-Code (Terraform, Pulumi or similar), and modern CI/CD practices • Strong understanding of microservices architecture, GitOps, observability, and platform automation using modern engineering tooling • Experience integrating AI or machine learning models into production systems using APIs, SDKs, or microservices • Knowledge of MLOps, cloud infrastructure, and supporting AI workloads in scalable production environments would be highly advantageous • Strong appreciation for platform security, cloud networking, data protection, and building highly resilient systems • Excellent communication skills with the ability to influence architectural decisions and collaborate effectively across engineering, product, and business teams Show more Show less