Kubernetes Certified Azure DevOps & MLOps Engineer

We are looking for Azure DevOps & MLOps Engineer to design, automate, and manage cloud-native platforms supporting modern AI/ML applications. The role requires strong expertise in AWS, Kubernetes, CI/CD, GitOps, observability, and deployment of AI/Agentic workloads.

Key Responsibilities

• Manage and operate Azure AKS/Kubernetes platforms.

• Build and maintain CI/CD pipelines using GitHub Actions, TeamCity, and ArgoCD.

• Deploy and support AI/ML/Agentic applications on AWS.

• Implement GitOps and infrastructure automation practices.

• Manage services like IAM, ACR, Blog storage, and networking.

• Build observability solutions using OpenTelemetry, CloudWatch, Grafana, Loki, and Splunk.

• Implement secure, scalable, and compliant cloud architectures.

• Support AI platforms involving LLM Gateways, Model APIs, Bedrock, SageMaker, and distributed workloads.

• Collaborate with development, security, platform, and data teams.

• Troubleshoot infrastructure, deployment, performance, and security issues.

• Mentor junior engineers and contribute to platform best practices.

Required Skills Must Have

• 4+ years of experience in DevOps, Cloud Engineering, or Platform Engineering.

• Strong hands-on experience with Kubernetes (EKS preferred).

• Experience with ArgoCD and GitOps workflows.

• Expertise in Azure services and IAM.

• CI/CD experience using GitHub Actions, Azure DevOps, or TeamCity.

• Experience with Terraform or Infrastructure as Code.

• Good understanding of cloud security and compliance.

MLOps / AIOps Experience (Any one)

• Azure Doc Intelligence

• MLflow

• Kubeflow

• Airflow

• Bedrock

• AgentCore

Good to Have

• Experience with Celery, LLM Gateway, Model Serving, and AI workload deployment.

• Python or Bash scripting.

• Knowledge of GxP, HIPAA, or EU AI Act requirements.

Certifications Mandatory (At least one)

• CKA / CKAD / CKS

Preferred

• Terraform Associate

• Azure certification