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DevOps Cloud Engineer

1 month ago

Singapore ARGYLL SCOTT CONSULTING PTE. LTD. Full time
Roles & Responsibilities

We are seeking a skilled and innovative DevOps Cloud Engineer to join our client. This is 2 year direct contract role to start with a potential to extend/get converted to a permanent role in future.

Job Overview:

This role involves working closely with AI and data science teams to build and maintain robust cloud-based solutions that enhance our AI-driven initiatives. The ideal candidate will be well-versed in cloud infrastructure, DevOps practices, and automation tools to support the deployment and management of AI models and other critical applications in the cloud.

Key Responsibilities:

  • Design, implement, and maintain cloud infrastructure for AI applications, ensuring scalability, security, and efficiency.
  • Automate deployment pipelines using tools like CI/CD, Terraform, and Ansible to streamline AI model deployment and updates.
  • Work closely with the AI Lab team to integrate machine learning models and data-driven solutions into the cloud environment.
  • Build and manage cloud environments on platforms like AWS, Azure, or Google Cloud to support high-performance computing for AI workloads.
  • Ensure the availability, performance, and reliability of AI-driven applications in production by implementing monitoring and logging solutions.
  • Collaborate with cross-functional teams to ensure smooth, continuous integration and delivery (CI/CD) pipelines for AI models and applications.
  • Optimize cloud resource usage and costs while maintaining best practices for cloud security and compliance.
  • Troubleshoot and resolve infrastructure issues quickly to minimize downtime and ensure the seamless operation of AI systems.

Requirements:

  • Proven experience as a DevOps Engineer, Cloud Engineer, or similar role with a strong focus on cloud infrastructure and automation.
  • Hands-on experience with major cloud platforms (AWS, Azure, or Google Cloud).
  • Proficiency in CI/CD pipelines, containerization technologies (Docker, Kubernetes), and infrastructure-as-code tools (e.g., Terraform, CloudFormation).
  • Familiarity with AI/ML models deployment processes and integration into production environments.
  • Solid understanding of cloud security practices and industry standards.
  • Strong scripting skills in languages such as Python, Bash, or Shell.
  • Excellent problem-solving and troubleshooting skills, with a focus on performance and scalability.
  • Ability to work in a fast-paced, collaborative environment with cross-functional teams.
  • Experience with monitoring tools (e.g., Prometheus, Grafana) and logging systems (e.g., ELK Stack).

Preferred Qualifications:

  • Experience working with AI/ML teams and understanding of their specific infrastructure needs.
  • Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, Azure DevOps Engineer).

Argyll Scott Consulting Pte Ltd

Tell employers what skills you have

Troubleshooting
Scalability
Kubernetes
Azure
Pipelines
Architect
Automation Tools
Scripting
Reliability
Compliance
Python
Google Cloud
Continuous Integration
Docker
Consulting
Ansible