AI DevOps Engineer (MLOps & Cloud)

DXC Technology Inc.; Petaling Jaya; On-site; MYR 100,000 - 150,000; Full time

Job summary

DXC Technology Inc. is seeking an experienced DevOps Engineer in Petaling Jaya, Malaysia. The ideal candidate will design and maintain scalable cloud infrastructure for AI/ML solutions and build Infrastructure as Code using tools like Terraform.

Applicants should have over 5 years of related experience, especially in MLOps and deployment of AI systems. Strong expertise in CI/CD and cloud platforms (AWS, Azure) is required. The role offers a collaborative, agile work environment with a strong focus on automation.

Qualifications

• 5+ years of experience in DevOps, SRE, or platform engineering.
• Strong knowledge of MLOps and AI solution deployment.
• Proficiency in cloud platforms and AI services.

Responsibilities

• Design and maintain scalable cloud infrastructure for AI/ML.
• Build Infrastructure as Code using Terraform or CloudFormation.
• Develop CI/CD pipelines for AI applications.

Skills

DevOps experience

MLOps knowledge

Cloud platforms knowledge

Infrastructure as Code

Containerization

CI/CD experience

Scripting skills

Monitoring tools knowledge

DevSecOps practices

Tools

Terraform

AWS

Azure

GCP

Docker

Kubernetes

GitHub Actions

Grafana

Prometheus

Job description

Key Responsibilities

• Design, implement, and maintain scalable, secure cloud infrastructure for AI/ML solutions
• Build and manage Infrastructure as Code (IaC) using tools such as Terraform or CloudFormation
• Develop and maintain CI/CD pipelines for AI applications and model deployment
• Support end‑to‑end MLOps lifecycle (training, versioning, deployment, monitoring)
• Automate deployments using best practices (blue/green, canary releases, rollback strategies)
• Configure monitoring, alerting, and observability (logs, metrics, tracing) for production systems
• Optimize performance, scalability, and cost (compute, storage, GPU usage)
• Use AI tools (e.g. Copilot, ChatGPT, Claude, Cursor) to accelerate scripting, automation, and incident resolution
• Troubleshoot production issues and ensure high system reliability and availability
• Support developers and data scientists on DevOps tooling and best practices
• Implement DevSecOps standards, including security, secrets management, and compliance
• Maintain clear technical documentation for infrastructure and processes

Skills & Experience

• 5+ years of experience in DevOps, SRE, or platform engineering
• Strong experience in MLOps and deployment of AI/ML solutions in production
• Proficiency with cloud platforms (AWS, Azure, or GCP) and related AI services
• Expertise in Infrastructure as Code (Terraform, CloudFormation, ARM templates)
• Hands‑on experience with containerization and orchestration (Docker, Kubernetes, Helm)
• Strong CI/CD experience (GitHub Actions, GitLab CI, Jenkins, Azure DevOps)
• Familiarity with MLOps tools (MLflow, Kubeflow, Weights & Biases, SageMaker Pipelines)
• Proficiency in scripting and automation (Python, Bash)
• Experience with monitoring and observability tools (Prometheus, Grafana, ELK, Datadog)
• Knowledge of DevSecOps practices and security standards
• Experience with secrets and configuration management (Vault, AWS Secrets Manager)

Preferred Skills & Attributes

• Experience optimising AI workloads using GPUs
• Ability to diagnose and resolve issues using AI‑assisted tools
• Strong problem‑solving and analytical thinking
• Pragmatic approach balancing automation, speed, and reliability
• Attention to detail in infrastructure design and security
• Proactive, with strong ownership and initiative
• Strong collaboration and support mindset
• Comfortable working in fast‑paced, agile environments

Work Environment

• Agile, fast‑paced innovation environment
• Close collaboration with AI engineers, data scientists, and infrastructure teams
• Strong focus on automation, scalability, and production‑ready AI systems
• English‑speaking environment (fluency required)