Deployment & Operations Engineer

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

Job summary

GTS Consulting in Singapore is seeking a Deployment & Operations Engineer to manage production deployments of our AI platform across cloud and on‑prem environments.

You will build and maintain CI/CD pipelines, monitor system performance, ensure high availability, and optimize costs while staying compliant with security standards.

The role requires hands-on experience with AWS/Azure, Kubernetes, and multi-region deployments to support scalable AI operations.

Qualifications

• Proficient in AWS and Azure cloud platforms.
• Experience with Kubernetes containerization.
• Skilled in deploying solutions across cloud and on-prem infrastructures.
• Background in AI platform operations or large-scale deployments.
• Ability to support deployments in multiple regions/environments.

Responsibilities

• Deploy the AI platform to production environments across cloud and on-prem.
• Ensure system stability, scalability, and adaptability to evolving needs.
• Establish and maintain CI/CD pipelines for deployments.
• Monitor performance and handle incidents to ensure high availability.
• Meet SLA targets across environments.
• Optimize operational costs and maintain security compliance.
• Select deployment solutions based on business requirements.
• Support multi-region deployments for large-scale AI platforms.

Skills

AWS

Azure

Kubernetes

CI/CD

Multi-environment deployment

Job description

Position: Deployment & Operations Engineer

Key Responsibilities

• Deploy the AI platform to production environments, including cloud GPU, managed services, and future on-premise or self-hosted deployments.
• Ensure system stability, scalability, and adaptability to meet evolving business needs.
• Establish and maintain CI/CD pipelines to streamline deployment processes.
• Monitor system performance and handle incidents to ensure high availability and reliability.
• Ensure Service Level Agreements (SLA) are met across all environments.
• Optimize operational costs and maintain security compliance.
• Select and implement optimal deployment solutions based on specific business requirements.
• Support multi-region and multi-environment deployments for large-scale AI platforms or systems.

Requirements

• Proficient in cloud platforms such as AWS and Azure.
• Experienced with containerization technologies, particularly Kubernetes.
• Capable of deploying solutions across both cloud and on-premise infrastructures.
• Demonstrated experience in AI platform operations or managing large-scale system deployments.
• Ability to support and maintain deployments in multiple regions and environments.