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Cloud Architecture & Engineering Workstream Lead (Singapore)
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AI Summary
Join a small engineering team building infrastructure for AI model training and evaluation. Own reliability, scale, performance, and developer experience of core platform systems. Requires at least 2 years of platform, backend, or infrastructure experience with AWS and containerized systems.
Key Highlights
Own reliability, scale, performance, and developer experience of core platform systems
Build and maintain AWS infrastructure with Terraform, Kubernetes/EKS, Docker, and related services
Improve scale through autoscaling, queueing, retries, rollback paths, and cleanup jobs
Build CI/CD, deployment automation, observability, and on-call workflows
Write production code for infrastructure automation and internal tools
Key Responsibilities
Own uptime, latency, provisioning speed, infrastructure costs, and incident response for production platform services
Build and maintain AWS infrastructure using Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management
Improve systems for scale through capacity planning, autoscaling, queueing, backpressure, cleanup jobs, retries, and rollback paths
Develop dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows
Build CI/CD, release automation, environment management, and safe deployment workflows
Write production code to automate infrastructure, improve backend services, and build internal tools
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Technical Skills Required
Benefits & Perks
Visa sponsorship
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Nice to Have
AI/ML platform or software engineering experience, ideally involving data-heavy systems, bursty workloads, long-running jobs, sandboxed execution, or distributed workers
Job Description
About the Role
Join a small engineering team building infrastructure for AI model training and evaluation. In this backend-focused role, you will own the reliability, scale, performance, and developer experience of core platform systems.
What You'll Do
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