Cloud Platform Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Cloud Platform Engineer based in Saudi Arabia. As a Cloud Platform Engineer, you will design, build, and operate scalable cloud infrastructure that enables AI applications, intelligent agents, and data products to move from prototype to production. You will join a central AI team supporting a major international logistics organization, contributing to cloud-native solutions across multiple countries. With a primary focus on Microsoft Azure and exposure to AWS, you will develop reliable infrastructure, deployment workflows, and observability frameworks that accelerate innovation. You will collaborate with AI engineers, data specialists, and international IT teams to establish secure, automated, and cost-efficient cloud environments. Your work will help streamline infrastructure provisioning, strengthen operational resilience, and enable the adoption of advanced AI-driven solutions at scale. This remote opportunity is ideal for a technically strong engineer who enjoys platform automation, cloud architecture, and solving complex challenges in a collaborative, international environment. Accountabilities • Design, build, and maintain cloud-native infrastructure supporting AI applications, intelligent agents, APIs, data pipelines, and data products, primarily using Microsoft Azure and, where required, AWS. • Develop reusable infrastructure-as-code modules, deployment templates, and observability patterns to standardize cloud environments and accelerate development. • Automate infrastructure provisioning, continuous integration and continuous delivery (CI/CD), monitoring, logging, secrets management, and cloud cost controls. • Contribute to cloud architecture decisions for AI-powered workflows, agentic systems, event-driven services, and modern data platforms. • Implement and maintain cloud security standards covering identity and access management, encryption, resilience, and secure infrastructure configuration. • Establish reliable monitoring, alerting, troubleshooting, and operational practices to improve platform availability, performance, and maintainability. • Collaborate with country-level IT teams and cross-functional stakeholders to onboard cloud environments, resolve deployment issues, and scale successful use cases across international operations. • Support the transition of AI and data solutions from development and experimentation into secure, scalable, production-ready environments. • Apply DevSecOps, platform engineering, and site reliability engineering principles to improve automation, consistency, and operational efficiency. • Leverage AI-assisted development tools to improve engineering productivity, code quality, and infrastructure delivery workflows. Requirements • Proven hands-on experience developing, deploying, and operating cloud-native applications and infrastructure, ideally with strong expertise in Microsoft Azure and practical exposure to AWS. • Solid experience with infrastructure as code (IaC), CI/CD pipelines, container technologies, cloud automation, monitoring, and logging solutions. • Strong programming skills in Python and SQL, with familiarity with TypeScript considered an advantage. • Understanding of data engineering fundamentals, including ETL processes, data pipelines, storage solutions, and system integrations. • Knowledge of cloud architecture, distributed systems, API-based services, and event-driven application design. • Familiarity with cloud security best practices, including identity management, access controls, encryption, and resilient infrastructure design. • Experience working with cross-functional and geographically distributed teams, with the ability to collaborate effectively across technical disciplines and international locations. • Comfortable using AI-powered coding assistants such as GitHub Copilot, Cursor, or similar tools to enhance development workflows. • Fluency in English, with strong communication skills and the ability to explain technical concepts and collaborate with stakeholders from different backgrounds. • A proactive, analytical mindset, with strong troubleshooting abilities and a commitment to automation, continuous improvement, and reliable engineering practices. Additional Assets That Would Be Advantageous • Experience with Snowflake, Azure AI Foundry, LangChain, Model Context Protocol (MCP), or comparable AI development and integration tools. • Familiarity with DevSecOps methodologies, platform engineering, and site reliability engineering (SRE) practices. • Relevant cloud certifications, particularly in Azure or AWS. • Experience developing frontend applications, internal developer portals, or self-service infrastructure platforms. Benefits • 100% remote work: Enjoy the flexibility to work remotely in an environment that supports your productivity and work-life balance, subject to employment and location eligibility. • International career opportunities: Collaborate with distributed teams and contribute to projects across multiple countries and international markets. • Professional development: Expand your expertise in cloud infrastructure, AI platforms, data engineering, and modern software delivery practices. • Collaborative work environment: Join a dynamic, professional team that values technical excellence, innovation, knowledge sharing, and teamwork. • Health insurance: Access health insurance benefits, subject to applicable employment terms and local eligibility. • Life insurance: Benefit from life insurance coverage, subject to the applicable policy and eligibility conditions. • Visa support: Potential assistance with work authorization through an eligible Tech Visa arrangement, where applicable. Specific eligibility for candidates based in India should be confirmed during the hiring process. • Exposure to emerging technologies: Work on cloud foundations that support AI agents, data products, and advanced digital solutions in a large-scale international environment. How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring d

Proven hands-on experience developing, deploying, and operating cloud-native applications and infrastructure, ideally with strong expertise in Microsoft Azure and practical exposure to AWS. Solid experience with infrastructure as code (IaC), CI/CD pipelines, container technologies, cloud automation, monitoring, and logging solutions. Strong programming skills in Python and SQL, with familiarity with TypeScript considered an advantage. Understanding of data engineering fundamentals, including ETL processes, data pipelines, storage solutions, and system integrations. Knowledge of cloud architecture, distributed systems, API-based services, and event-driven application design. Familiarity with cloud security best practices, including identity management, access controls, encryption, and resilient infrastructure design. Experience working with cross-functional and geographically distributed teams, with the ability to collaborate effectively across technical disciplines and international locations. Comfortable using AI-powered coding assistants such as GitHub Copilot, Cursor, or similar tools to enhance development workflows. Fluency in English, with strong communication skills and the ability to explain technical concepts and collaborate with stakeholders from different backgrounds. A proactive, analytical mindset, with strong troubleshooting abilities and a commitment to automation, continuous improvement, and reliable engineering practices.

Design, build, and maintain cloud-native infrastructure supporting AI applications, intelligent agents, APIs, data pipelines, and data products, primarily using Microsoft Azure and, where required, AWS. Develop reusable infrastructure-as-code modules, deployment templates, and observability patterns to standardize cloud environments and accelerate development. Automate infrastructure provisioning, continuous integration and continuous delivery (CI/CD), monitoring, logging, secrets management, and cloud cost controls. Contribute to cloud architecture decisions for AI-powered workflows, agentic systems, event-driven services, and modern data platforms. Implement and maintain cloud security standards covering identity and access management, encryption, resilience, and secure infrastructure configuration. Establish reliable monitoring, alerting, troubleshooting, and operational practices to improve platform availability, performance, and maintainability. Collaborate with country-level IT teams and cross-functional stakeholders to onboard cloud environments, resolve deployment issues, and scale successful use cases across international operations. Support the transition of AI and data solutions from development and experimentation into secure, scalable, production-ready environments. Apply DevSecOps, platform engineering, and site reliability engineering principles to improve automation, consistency, and operational efficiency. Leverage AI-assisted development tools to improve engineering productivity, code quality, and infrastructure delivery workflows.