Azure Devops Engineer with MLOps

Job Summary

We are seeking a highly skilled DevOps Engineer with strong expertise in Azure Cloud, Kubernetes, Infrastructure as Code, CI/CD automation, and cloud security practices. The ideal candidate will also bring hands-on experience in MLOps and LLMOps, supporting model deployment, automation pipelines, and GPU-based workload optimization.

Key Responsibilities

Cloud & Infrastructure

1. Design, implement, and manage DevOps solutions in Microsoft Azure.
2. Demonstrate strong understanding of Azure cloud infrastructure services and their limitations.
3. Configure and monitor application performance, scaling strategies, and auto scale-up/scale-down mechanisms.
4. Provide best practices for provisioning production and non-production environments to optimize cloud usage and costs.
5. Proactively identify and remediate vulnerabilities within the Azure ecosystem.
6. Manage secure credential handling using tools such as HashiCorp Vault or Azure Key Vault.

Containerization & Kubernetes

1. Manage and scale production-grade Kubernetes clusters (AKS / OpenShift).
2. Develop and implement containerization strategies using Docker and Kubernetes.
3. Implement and manage serverless solutions within Azure.
4. Ensure strong understanding of microservices architecture and API communication in containerized environments.

CI/CD & GitOps

1. Implement declarative, automated application deployments using GitOps principles with ArgoCD.
2. Maintain and enhance CI/CD pipelines using Bamboo and Tekton.
3. Configure webhooks and build triggers for CI pipelines.
4. Integrate automated security scanning (SAST/DAST) and container image signing into the build process.

Infrastructure as Code

1. Develop and manage infrastructure using Terraform.

Security & Monitoring

1. Implement security best practices across cloud infrastructure.
2. Work with system, security, and network monitoring tools.
3. Ensure compliance and continuous monitoring of infrastructure and applications.

Operations & Reliability

1. Demonstrate strong understanding of application architecture and common failure modes.
2. Support 24x7 application operations including:
3. Incident Management
4. Change Management
5. Capacity Management

MLOps & LLMOps Responsibilities

1. Model Deployment: Build and manage infrastructure to support LLM serving, fine-tuning, and monitoring.
2. Pipeline Automation: Apply MLOps principles to automate data versioning and model training workflows.
3. Resource Optimization: Manage GPU-intensive workloads and optimize compute costs within Azure environments.

Required Skills & Qualifications

1. Proven experience in DevOps within Azure Cloud environments.
2. Hands-on expertise in Kubernetes (AKS/OpenShift), Docker, and serverless architectures.
3. Strong experience with Terraform (Infrastructure as Code).
4. Experience with CI/CD tools such as Bamboo, Tekton, and GitOps tools like ArgoCD.
5. Understanding of cloud security, vulnerability management, and automated security testing (SAST/DAST).
6. Experience handling production environments and large-scale distributed systems.
7. Exposure to MLOps / LLMOps practices is highly preferred.