DevOps Engineer, AI/ML Ops & Cloud Reliability

Digile Pte Ltd; Kuala Lumpur; On-site; MYR 120,000 - 240,000; Full time

Job summary

Digile’s AI Practice seeks a DevOps Engineer with an MLOps focus to join the shared engineering pool supporting Forward Deployed Engineer pods that turn AI capabilities into production-grade workflows with measurable business impact.

The main duties include owning deployment, infrastructure and reliability for AI workflows, collaborating with Senior/Junior FDEs and AI Product Managers across pods to ensure deployable, monitorable and governable pipelines.

Qualifications

• 3–5 years of experience in DevOps, SRE, platform or cloud engineering with exposure to MLOps or LLMOps.
• Experience deploying/operating production apps on Azure, AWS or Google Cloud.
• Experience running containerised workloads with Docker and Kubernetes.
• Experience implementing security and compliance controls in enterprise or regulated environments.

Responsibilities

• Design, build and maintain CI/CD pipelines for AI workflows, including versioning of prompts and configurations.
• Set up and manage cloud infrastructure/environments (dev, staging, prod) using Infrastructure as Code.
• Implement monitoring, logging and alerting, including LLM observability (tracing/latency/cost).
• Maintain uptime, drift and error rate targets and perform root cause analysis.

Skills

CI/CD pipelines

Docker & Kubernetes

Cloud platforms

Security & compliance

Scripting (Bash/Python)

RBAC & IAM

Observability tools

Data governance

API gateways

Terraform

Tools

GitHub Actions

GitLab CI

Azure DevOps

Terraform

Bicep

CloudFormation

Job description

Digile’s AI Practice seeks a DevOps Engineer with an MLOps focus to join the shared engineering pool supporting Forward Deployed Engineer pods that turn AI capabilities into production-grade workflows with measurable business impact.

The main duties include owning deployment, infrastructure and reliability for AI workflows, collaborating with Senior/Junior FDEs and AI Product Managers across pods to ensure deployable, monitorable and governable pipelines.