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DevOps Engineer (AI Infrastructure)
Job summary
A fast-growing digital agency is seeking a skilled DevOps Engineer in Singapore to manage CI/CD pipelines and cloud infrastructure for AI-powered products. You will set up and maintain systems, ensuring scalability and security, while collaborating with cross-functional teams. Ideal candidates have robust experience with AWS or GCP, solid CI/CD knowledge, and familiarity with Docker and Kubernetes. The role offers growth opportunities in a dynamic environment. Join us to work on impactful AI products.
Benefits
Qualifications
- 3+ years of DevOps or relevant infrastructure experience required.
- Hands-on experience with AWS and GCP is preferred.
- Solid understanding of CI/CD and tools like GitHub Actions or Jenkins.
- Experience with Docker and Kubernetes is essential.
Responsibilities
- Design and maintain CI/CD pipelines for AI/ML workflows.
- Manage cloud infrastructure focusing on scalability and security.
- Automate data pipelines with AI engineers and software developers.
- Implement infrastructure as code using tools like Terraform.
Skills
Tools
We are a fast-growing digital agency building AI-powered products. Our AI team is expanding, and we are looking for a skilled DevOps Engineer to help us scale, automate, and secure our infrastructure.
You will be responsible for setting up and managing the CI/CD pipelines, infrastructure automation, and cloud environments that power our AI/ML workflows. This role is ideal for someone who thrives in fast-paced environments and is excited by the challenge of enabling scalable AI product delivery.
- Design, implement, and maintain CI/CD pipelines for AI models, APIs, and supporting applications.
- Set up and manage cloud infrastructure (AWS, GCP, or equivalent) with a strong focus on scalability, cost optimization, and security.
- Support containerized environments using Docker and Kubernetes (EKS, GKE, etc.).
- Work closely with AI engineers and software developers to automate data pipelines, model training/deployment, and monitoring.
- Implement and maintain infrastructure as code (IaC) using tools like Terraform or Pulumi.
- Monitor system performance, troubleshoot production issues, and ensure system reliability and uptime.
- Enforce best practices in DevOps, security, versioning, and documentation.
- 3+ years of DevOps, Site Reliability Engineering, or relevant infrastructure experience.
- Strong hands-on experience with cloud providers (AWS and GCP preferred).
- Solid understanding of CI/CD principles and experience with tools like GitHub Actions, GitLab CI, or Jenkins.
- Experience with Docker, Kubernetes, and container orchestration.
- Familiarity with IaC tools such as Terraform, CloudFormation, or Pulumi.
- Working knowledge of networking, security, and access control in cloud environments.
- Exposure to machine learning or AI deployment workflows is a strong plus.
- Comfortable collaborating with cross-functional teams including data scientists, backend engineers, and product managers.
- Experience deploying AI/ML pipelines with tools like MLflow, Airflow, or Kubeflow.
- Understanding of GPU/TPU setup and auto-scaling strategies for training/inference workloads.
- Monitoring and logging using Prometheus, Grafana, CloudWatch, or similar tools.
- Work on real AI products with tangible impact.
- Autonomy to shape and optimize our AI infrastructure.
- A collaborative and ambitious team, with leadership open to innovation and experimentation.
- Opportunities for growth and cross-disciplinary exposure across AI, web, and product development.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.