DevOps Engineer (AI Platform and Cloud)

NIVABIZ PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

NivaBiz is seeking an experienced DevOps Engineer to design, build, and operate scalable AI platforms that support deployment, management, and monitoring of AI and Generative AI solutions across enterprise environments.

The ideal candidate should have strong IaC with Terraform, CI/CD automation, cloud-native technologies, and solid understanding of AI/ML ecosystems within security-conscious environments.

Qualifications

• 3+ years in Cloud/DevOps or Infrastructure Automation.
• Hands-on with Terraform and IaC.
• Strong CI/CD pipeline design and implementation.
• Experience with Docker and Kubernetes.
• Proficiency in scripting languages e.g., Python/PowerShell/Bash.
• Knowledge of Git, version control, and software delivery practices.
• Experience with AI/ML platforms and MLOps is a plus.

Responsibilities

• Design, build, and operate scalable cloud infrastructure for AI platforms.
• Develop reusable Terraform modules and IaC standards.
• Automate CI/CD pipelines across multiple tools (Azure DevOps, GitHub Actions, GitLab CI/CD, Jenkins).
• Manage AI platform environments on Azure and AWS.
• Implement GitOps, DevSecOps, and security controls.
• Support lifecycle management of AI/ML applications, including MLOps.

Skills

Terraform

CI/CD

Docker

Kubernetes

Python PowerShell Bash

Education

Bachelor's or Diploma in IT/CS

Tools

Azure

AWS

Job description

JOB SUMMARY

NivaBiz is seeking an experienced DevOps Engineer to design, build, and operate scalable AI platforms that support the deployment, management, and monitoring of AI and Generative AI solutions across enterprise environments.

The ideal candidate should possess strong expertise in Infrastructure as Code using Terraform, CI/CD automation, cloud-native technologies, and a solid understanding of AI, Machine Learning, and Generative AI ecosystems.

The successful candidate will work closely with infrastructure engineers, application teams, cloud architects, security teams, and other stakeholders to deliver secure, reliable, and scalable AI platforms.

KEY RESPONSIBILITIES

• Design, implement, and maintain cloud infrastructure using Terraform and Infrastructure as Code principles.
• Build and manage AI platform environments across Microsoft Azure and 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/CD, or Jenkins.
• Automate build, testing, deployment, and release processes for AI and application workloads.
• Implement GitOps and DevSecOps best practices.
• Support the deployment and lifecycle management of AI, Machine Learning, 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 containerised 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, Identity and Access Management, secrets management, and compliance controls.
• Ensure platform reliability, observability, logging, and monitoring.
• Collaborate with security and governance teams to enforce enterprise standards.

REQUIREMENTS

• Diploma or Degree in Information Technology, Computer Engineering, or a related discipline.
• Minimum three 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 working with Docker and Kubernetes.
• Proficiency in at least one cloud platform: Microsoft 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 Large Language Models and Generative AI.
• Experience with Azure OpenAI Service, Azure Machine Learning, or AWS Bedrock.
• Knowledge of monitoring and observability tools such as Prometheus, Grafana, Azure Monitor, Datadog, or Splunk.
• AI, Cloud, Kubernetes, Terraform, or DevOps certifications will be advantageous.
• Good working knowledge of DevOps, GitHub Actions, GitLab CI/CD, Jenkins, Git, Docker, and Kubernetes.