AI Cloud Infrastructure Engineer

📋 Description

• • Join Time Base Technology Limited as an AI Cloud Infrastructure Engineer and play a pivotal role in shaping the future of AI-driven productivity and creativity. We are on a mission to reimagine how individuals interact with information, merging human ingenuity with cutting-edge AI capabilities. This is your chance to contribute to a platform that empowers millions of users worldwide to explore new dimensions of productivity, creativity, and learning, transforming digital note-taking into an inspiring and innovative experience.
• • As part of our fast-growing and talented Backend AI Team, you will be instrumental in building a modern, robust, and scalable platform that accelerates the rollout of innovative AI features. We believe in automating ourselves out of our jobs, which, paradoxically, fuels our growth and creates exciting new opportunities. This role is ideal for a junior to mid-level engineer early in their DevOps journey, offering a unique opportunity to work closely with experienced mentors.
• • This position is based in the Asia timezone, with the flexibility of remote work or joining us in our Singapore office. You will contribute to providing around-the-sun coverage, significantly reducing reliance on single points of expertise, and enhancing overall system resiliency through collaborative peer reviews and continuous operational improvements.
• • Your core responsibilities will encompass the design, build, and maintenance of our critical infrastructure, ensuring it adheres to the highest standards of reliability, specifically aligning with Dickerson’s Hierarchy of Reliability. You will be at the forefront of building and optimizing CI/CD pipelines tailored for AI Infrastructure workloads, ensuring efficient and rapid deployment of new features and models.
• • You will evolve into a go-to person for higher-level escalations for our AI applications, demonstrating a deep understanding of system behavior and troubleshooting complex issues. A key focus will be on enhancing our system monitoring, health reporting, and logging capabilities. This includes refining platform and application alerts across all global regions and features to ensure proactive issue detection and resolution.
• • Security will be a paramount concern. You will design and implement robust security measures, actively assisting in maintaining stringent information security practices and procedures. This involves staying ahead of threats by updating platform versions, patching security packages promptly, and continuously optimizing infrastructure costs without compromising security or performance.
• • You will actively contribute to offloading initiatives for new AI projects, such as developing and managing self-hosted inference and training platforms. Furthermore, you will significantly improve the Backend Developer Experience (DevEx) through constructive peer reviews and the implementation of automation solutions.
• • Initially, you will gain hands-on experience by reviewing existing systems under the guidance of experienced mentors. As you grow, you will transition into a Direct Responsible Individual (DRI) for larger, impactful projects in infrastructure, automation, and Backend AI DevEx, potentially including AI reviews or FinOps initiatives.
• • Your performance will be evaluated based on key metrics such as VictorOps SLA adherence, the speed of issue resolution and upgrades, and the minimization of system downtime, directly contributing to our operational excellence.
• • This role offers exceptional growth prospects within a highly collaborative and supportive environment. You will have a direct impact on global operational efficiency and the overall resiliency of our AI infrastructure, working with a tech stack that includes Datadog for monitoring and logging, Terraform for Infrastructure-as-Code managed via Atlantis, GitHub Actions for CI/CD, and Kubernetes (EKS) managed with ArgoCD/Argo Rollout and Helm for deployments.
• • You will gain exposure to cutting-edge AI infrastructure, including integrations with external AI providers, managing large-scale backends with agentic applications, and developing self-hosted inference and training platforms. This is an opportunity to be at the heart of innovation in AI and cloud infrastructure.