Job Overview
We are looking for an experienced DevOps Engineer to design, implement, and support enterprise AI platforms that power Artificial Intelligence (AI) and Generative AI solutions. This role is ideal for professionals with strong cloud infrastructure, automation, and DevOps expertise who are passionate about building scalable, secure, and high-performing platforms.
You will work closely with cloud architects, infrastructure engineers, and application teams to automate deployments, optimize platform performance, and enable AI applications across cloud environments.
Key Responsibilities
Cloud Infrastructure & Automation
- Design, deploy, and maintain cloud infrastructure using Infrastructure as Code (IaC) methodologies.
- Develop reusable infrastructure modules and standardize cloud deployment practices.
- Automate infrastructure provisioning to improve scalability, reliability, and operational efficiency.
- Support enterprise cloud environments across Microsoft Azure and AWS.
DevOps & CI/CD
- Build, maintain, and optimize CI/CD pipelines for application and AI platform deployments.
- Automate software build, testing, deployment, and release processes.
- Implement DevOps, GitOps, and DevSecOps best practices to improve delivery quality and security.
- Maintain version control and release management processes.
AI Platform & MLOps
- Support the deployment and ongoing management of AI, Machine Learning (ML), and Generative AI applications.
- Implement MLOps practices including model deployment, version control, monitoring, and governance.
- Integrate enterprise AI services and cloud-based AI platforms into production environments.
Container & Platform Management
- Deploy and administer containerized applications using Docker and Kubernetes.
- Maintain highly available Kubernetes clusters supporting enterprise workloads.
- Monitor and optimize container platform performance, availability, and security.
Security & Platform Operations
- Implement cloud security controls including identity management, access policies, and secrets management.
- Monitor platform health, logging, observability, and system performance.
- Troubleshoot infrastructure, deployment, and platform-related issues.
- Partner with security and governance teams to ensure compliance with enterprise standards.
Requirements
- Diploma or Degree in Information Technology, Computer Science, Computer Engineering, or a related discipline.
- At least 3 years of experience in DevOps, Cloud Engineering, Platform Engineering, or Infrastructure Automation.
- Hands-on experience with Terraform and Infrastructure as Code (IaC).
- Strong knowledge of CI/CD pipeline implementation and automation.
- Experience managing container platforms using Docker and Kubernetes.
- Experience working with Microsoft Azure and/or Amazon Web Services (AWS).
- Proficiency in scripting languages such as Python, PowerShell, Bash, or Shell scripting.
- Good understanding of Git, version control, and modern software delivery practices.
- Exposure to AI/ML platform deployment and MLOps concepts.
- Knowledge of Generative AI technologies, Large Language Models (LLMs), or enterprise AI services will be an advantage.
- Experience with cloud monitoring and observability tools such as Prometheus, Grafana, Azure Monitor, Datadog, or Splunk is preferred.
- Relevant certifications in Cloud, DevOps, Kubernetes, Terraform, or AI is advantageous.