About This Role
This engineering role focuses on designing, building, and operating scalable cloud infrastructure to enable AI applications, intelligent agents, and data products to move from prototype to production. Joining a central AI team, you will support a major international logistics organization by contributing to cloud-native solutions across multiple countries, primarily using Microsoft Azure with exposure to AWS. The position is remote and ideal for a technically strong engineer who enjoys platform automation, cloud architecture, and solving complex challenges in a collaborative, international environment.
Responsibilities
- 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
