AI DevOps Engineer

GTS Consulting; Singapore; On-site; SGD 100,000 - 180,000; Full time

Job summary

GTS Consulting in Singapore is seeking an experienced DevOps Engineer to own the deployment of an AI platform into production across cloud GPU infrastructure and eventual on-premise environments.

You will build and maintain CI/CD pipelines, monitor performance, respond to incidents, and uphold SLAs while optimizing costs and security. Proficiency in AWS/Azure, Docker, and Kubernetes is required, with hands-on AI/ML tooling experience.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field or equivalent practical experience.
• Proven experience in DevOps engineering with a focus on AI/ML workflows and infrastructure.
• Strong proficiency in cloud platforms such as AWS, Azure, or Google Cloud with cloud-native services.
• Hands-on experience with Docker and Kubernetes for orchestration and deployment.
• Proficiency in scripting with Python, Bash, or Go.
• Experience with CI/CD tools Jenkins, GitLab CI/CD, or CircleCI.
• Familiarity with AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Strong networking, security, and system administration fundamentals.
• Excellent problem-solving and cross-functional collaboration abilities.

Responsibilities

• Own the deployment of the AI platform into production across cloud GPU infrastructure, managed services, and future on-premise or self-hosted environments.
• Build and maintain CI/CD pipelines, monitor performance, respond to incidents, and uphold SLAs with cost and security optimization.
• Leverage cloud platforms (AWS/Azure) and Kubernetes to deploy across cloud and on-premise setups, selecting best-fit solutions.
• Demonstrate experience operating AI platforms or large-scale systems with multi-region/multi-environment support.

Skills

DevOps

AI/ML workflows

Cloud platforms

CI/CD

Scripting (Python/Bash/Go)

Docker

Kubernetes

Networking & security basics

Collaboration

Education

Bachelor's degree in Computer Science or related

Tools

Jenkins

GitLab CI/CD

CircleCI

TensorFlow

PyTorch

Scikit-learn

Job description

• Own the deployment of the AI platform into production across cloud GPU infrastructure, managed services, and future on‑premise or self‑hosted environments, maintaining stability, scalability, and the flexibility to adapt as business needs evolve.
• Build and maintain CI/CD pipelines, monitor system performance, respond to incidents, uphold SLAs, and drive cost and security optimization across all environments.
• Skilled in cloud platforms (e.g., AWS, Azure) and containerization (e.g., Kubernetes), with the ability to deploy across both cloud and on‑premise setups and select the best‑fit solution based on business needs.
• Proven experience operating AI platforms or large‑scale systems, including support for multi‑region and multi‑environment deployments.

Job Responsibilities

• Own the deployment of the AI platform into production across cloud GPU infrastructure, managed services, and future on‑premise or self‑hosted environments, maintaining stability, scalability, and the flexibility to adapt as business needs evolve.
• Build and maintain CI/CD pipelines, monitor system performance, respond to incidents, uphold SLAs, and drive cost and security optimization across all environments.
• Skilled in cloud platforms (e.g., AWS, Azure) and containerization (e.g., Kubernetes), with the ability to deploy across both cloud and on‑premise setups and select the best‑fit solution based on business needs.
• Proven experience operating AI platforms or large‑scale systems, including support for multi‑region and multi‑environment deployments.

Job Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Proven experience in DevOps engineering, with a focus on AI/ML workflows and infrastructure.
• Strong proficiency in cloud platforms such as AWS, Azure, or Google Cloud, including experience with cloud‑native services.
• Hands‑on experience with containerization and orchestration tools like Docker and Kubernetes.
• Proficiency in scripting and programming languages such as Python, Bash, or Go.
• Experience with CI/CD tools such as Jenkins, GitLab CI/CD, or CircleCI.
• Familiarity with AI/ML frameworks and tools such as TensorFlow, PyTorch, or Scikit‑learn.
• Strong understanding of networking, security, and system administration principles.
• Excellent problem‑solving skills and the ability to work collaboratively in a fast‑paced environment.
• Strong communication skills to effectively collaborate with cross‑functional teams.