Senior Software Engineer, Infrastructure
- AI
- Machine Learning
- Incident Response
- AWS
- Terraform
- Kubernetes
- EKS
- Helm
- Docker
- EC2
- IAM
- Secrets Management
- CI/CD
- AI/ML
- Visa support
About the Role
Join an engineering team building infrastructure for AI and machine learning workflows. In this backend-focused role, you will own the reliability, scale, performance, and developer experience of core platform systems, helping teams build and operate services more effectively.
What You'll Do
Own production 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.
Design platform and backend systems for scale, including capacity planning, autoscaling, queueing, backpressure, retries, cleanup jobs, and rollback paths.
Improve dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows to support fast detection and resolution of failures.
Build reliable CI/CD, release automation, environment management, and deployment workflows that improve developer productivity and reduce production risk.
Write maintainable production code to automate infrastructure, improve backend services, and create internal tools.
What We're Looking For
At least 2 years of experience in platform engineering, backend engineering, or infrastructure roles, with ownership of production cloud systems.
Production experience with AWS and containerized systems, including Terraform, Kubernetes/EKS, Docker, networking, load balancers, and secrets management.
Experience owning uptime, latency, and incident response, and building observability, CI/CD, release automation, and safe deployment workflows.
Strong backend engineering judgment across service architecture, APIs, databases, asynchronous systems, and production failure modes.
Experience with AI/ML platforms or software, or with data-heavy, workflow, marketplace, developer-tools, or enterprise systems.
Familiarity with bursty workloads, long-running jobs, sandboxed execution, distributed workers, or high-concurrency services is valuable.
A track record of improving infrastructure efficiency and cloud costs through architecture, autoscaling, workload placement, caching, or cleanup systems.
Compensation & Benefits
Salary range: USD 150,000 to 250,000 annually. Visa sponsorship is available.
Location
On-site in Singapore, Singapore.
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