About the Role
Join an engineering team building infrastructure for AI/ML training and evaluation platforms. You will own the reliability, scalability, performance, and developer experience of core systems that support high-concurrency workloads.
What You'll Do
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Own production uptime, latency, infrastructure provisioning, cloud costs, and incident response for core services.
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Build and maintain AWS infrastructure using Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management.
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Improve platform and backend systems through capacity planning, autoscaling, queueing, backpressure, retries, cleanup jobs, and safe rollback paths.
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Develop dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows to help teams detect and resolve failures quickly.
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Build CI/CD pipelines, release automation, environment management, and deployment workflows, along with production code and internal tools that improve engineering productivity.
What We're Looking For
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At least 2 years of experience in platform engineering, backend engineering, or infrastructure roles operating production cloud systems.
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Strong production experience with AWS, containers, Terraform, Kubernetes/EKS, Docker, networking, load balancers, and secrets management.
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Experience owning reliability and incident response, and building CI/CD, observability, and safe deployment systems.
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Solid backend engineering judgment across service architecture, APIs, databases, and asynchronous systems.
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AI/ML platform or software engineering experience, ideally with data-heavy workloads, distributed workers, long-running jobs, or high-concurrency services.
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A record of writing production code and improving infrastructure efficiency, scaling, or cloud costs.
Compensation & Benefits
Annual salary: USD 100,000 to USD 170,000. Visa sponsorship is available.
Location
On-site in Singapore, Singapore.
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