About the Role
Join a small engineering team building infrastructure for AI training and evaluation platforms. You will own the reliability, scale, performance, and developer experience of core systems, helping teams build and operate production services more effectively.
What You’ll Do

• Own uptime, latency, provisioning speed, infrastructure costs, and incident response for core platform services.

• Build and maintain AWS infrastructure using Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management.

• Improve platform and backend systems through capacity planning, autoscaling, queueing, backpressure, retries, cleanup jobs, and rollback paths.

• Develop dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows to support effective incident response.

• Build CI/CD, release automation, environment management, and safe deployment workflows.

• Write production code for infrastructure automation, backend services, and internal developer tools.

What We’re Looking For

• At least 2 years of experience in platform, backend, or infrastructure engineering, operating production cloud infrastructure.

• A degree in a technical field and strong software engineering fundamentals.

• Production experience with AWS and containerized systems, including Terraform, Kubernetes/EKS, Docker, networking, load balancers, and secrets management.

• Experience owning reliability and incident response, and building CI/CD, deployment, and observability systems.

• Strong backend knowledge across service architecture, APIs, databases, asynchronous systems, and production failure modes.

• AI/ML platform or software engineering experience, ideally with data-heavy systems, distributed workers, long-running jobs, or high-concurrency workloads.

• Evidence of writing maintainable production code and improving infrastructure efficiency, developer workflows, or cloud costs.

Compensation & Benefits
Base salary: $100,000 to $170,000 USD annually. Visa sponsorship is available.
Location
On-site in Singapore, Singapore.

About the Role
Join a small engineering team building infrastructure for AI training and evaluation platforms. You will own the reliability, scale, performance, and developer experience of core systems, helping teams build and operate production services more effectively.
What You’ll Do

• Own uptime, latency, provisioning speed, infrastructure costs, and incident response for core platform services.

• Build and maintain AWS infrastructure using Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management.

• Improve platform and backend systems through capacity planning, autoscaling, queueing, backpressure, retries, cleanup jobs, and rollback paths.

• Develop dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows to support effective incident response.

• Build CI/CD, release automation, environment management, and safe deployment workflows.

• Write production code for infrastructure automation, backend services, and internal developer tools.

What We’re Looking For

• At least 2 years of experience in platform, backend, or infrastructure engineering, operating production cloud infrastructure.

• A degree in a technical field and strong software engineering fundamentals.

• Production experience with AWS and containerized systems, including Terraform, Kubernetes/EKS, Docker, networking, load balancers, and secrets management.

• Experience owning reliability and incident response, and building CI/CD, deployment, and observability systems.

• Strong backend knowledge across service architecture, APIs, databases, asynchronous systems, and production failure modes.

• AI/ML platform or software engineering experience, ideally with data-heavy systems, distributed workers, long-running jobs, or high-concurrency workloads.

• Evidence of writing maintainable production code and improving infrastructure efficiency, developer workflows, or cloud costs.

Compensation & Benefits
Base salary: $100,000 to $170,000 USD annually. Visa sponsorship is available.
Location
On-site in Singapore, Singapore.