Devops Engineer - TOSS-EX PR PTE. LTD.

OpenTalent; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

OpenTalent seeks an experienced DevOps Engineer to design, build and operate scalable AI platforms enabling deployment, management and monitoring of AI solutions across the enterprise. You will work with infra engineers, application teams and cloud architects to deliver secure, reliable platforms using Terraform, CI/CD automation and cloud-native tech.

The role requires hands-on experience with Terraform, Docker, Kubernetes, Azure/AWS, and AI/ML workflows, plus strong scripting and monitoring

Qualifications

• Diploma or Degree in Information Technology, Computer Engineering, or related discipline.
• Minimum 3+ years of experience in Cloud Engineering, Platform Engineering, DevOps, or Infrastructure Automation.
• Hands-on experience with Terraform and Infrastructure as Code.
• Strong experience designing and managing CI/CD pipelines.
• Experience with Docker and Kubernetes.
• Proficiency in at least one cloud platform: Azure or AWS.
• Experience with scripting languages such as Python, PowerShell, Bash, or Shell scripting.
• Strong understanding of Git, version control, and software delivery best practices.
• Experience supporting AI/ML platforms and MLOps environments.
• Knowledge of LLMs, Generative AI
• Experience with: Azure OpenAI Service, Azure Machine Learning, AWS Bedrock
• Knowledge of monitoring and observability tools such as Prometheus, Grafana, Azure Monitor, Datadog, or Splunk.

Responsibilities

• Design, implement, and maintain cloud infrastructure using Terraform and IaC principles.
• Build and manage AI platform environments across Azure, AWS,
• Develop reusable Terraform modules and infrastructure standards.
• Implement infrastructure automation to improve scalability, reliability and operational efficiency.
• Design and maintain CI/CD pipelines using Azure DevOps, GitHub Actions, GitLab CI, or Jenkins.
• Automate build, test, deployment, and release processes for AI and application workloads.
• Implement GitOps and DevSecOps best practices.
• Support deployment and lifecycle management of AI/ML and Generative AI applications.
• Build and maintain MLOps capabilities including model deployment, versioning, monitoring, and governance.
• Enable integration with AI services such as Azure OpenAI, OpenAI APIs, Azure AI Services, AWS Bedrock, or Vertex AI.
• Deploy and manage containerized workloads using Docker and Kubernetes.
• Maintain scalable Kubernetes environments for AI and enterprise applications.
• Troubleshoot performance, security, and reliability issues within container platforms.
• Implement cloud security best practices, IAM, secrets management, and compliance controls.
• Ensure platform reliability, observability, logging, and monitoring.
• Collaborate with security and governance teams to enforce enterprise standards.

Skills

Terraform

CI/CD pipelines

Git

Scripting (Python/Bash)

Cloud platforms (Azure, AWS)

AI/ML & Generative AI concepts

DevSecOps & security

Observability & monitoring

Education

Diploma or Degree in IT/Comp Eng or related

Tools

Docker

Kubernetes

Azure OpenAI

AWS Bedrock

Prometheus

Grafana

Datadog

Splunk

Job description

Overview

Overview: (Summary of the role) We are seeking an experienced Devops Engineer to design, build and operate scalable AI platforms that enable the deployment, management and monitoring of AI and Generative AI solutions across the enterprise. The ideal candidate possesses strong expertise in Infrastructure as Code (Terraform), CI/CD automation, cloud-native technologies and a solid understanding of AI/ML and Generative AI ecosystems. You will work closely with infra engineers, application teams and cloud architects to deliver secure, reliable, and scalable AI platforms.

Responsibilities

• Design, implement, and maintain cloud infrastructure using Terraform and IaC principles.
• Build and manage AI platform environments across Azure, AWS,
• Develop reusable Terraform modules and infrastructure standards.
• Implement infrastructure automation to improve scalability, reliability and operational efficiency.
• Design and maintain CI/CD pipelines using Azure DevOps, GitHub Actions, GitLab CI, or Jenkins.
• Automate build, test, deployment, and release processes for AI and application workloads.
• Implement GitOps and DevSecOps best practices.
• Support deployment and lifecycle management of AI/ML and Generative AI applications.
• Build and maintain MLOps capabilities including model deployment, versioning, monitoring, and governance.
• Enable integration with AI services such as Azure OpenAI, OpenAI APIs, Azure AI Services, AWS Bedrock, or Vertex AI.
• Deploy and manage containerized workloads using Docker and Kubernetes.
• Maintain scalable Kubernetes environments for AI and enterprise applications.
• Troubleshoot performance, security, and reliability issues within container platforms.
• Implement cloud security best practices, IAM, secrets management, and compliance controls.
• Ensure platform reliability, observability, logging, and monitoring.
• Collaborate with security and governance teams to enforce enterprise standards.

Requirements

(Indicate the qualifications, education, associated training, background knowledge, skills and attributes to perform the job competently) JOB DESCRIPTION

• Diploma or Degree in Information Technology, Computer Engineering, or related discipline.
• Minimum 3+ years of experience in Cloud Engineering, Platform Engineering, DevOps, or Infrastructure Automation.
• Hands-on experience with Terraform and Infrastructure as Code.
• Strong experience designing and managing CI/CD pipelines.
• Experience with Docker and Kubernetes.
• Proficiency in at least one cloud platform: Azure or AWS
• Experience with scripting languages such as Python, PowerShell, Bash, or Shell scripting.
• Strong understanding of Git, version control, and software delivery best practices.
• Experience supporting AI/ML platforms and MLOps environments.
• Knowledge of LLMs, Generative AI
• Experience with: Azure OpenAI Service, Azure Machine Learning, AWS Bedrock
• Knowledge of monitoring and observability tools such as Prometheus, Grafana, Azure Monitor, Datadog, or Splunk.