DevOps Specialist

Job Title : DevOps Specialist

Role Summary :

The DevOps Specialist will architect, implement, and maintain the automated infrastructure and deployment pipelines that facilitate continuous delivery on the Microsoft Azure cloud platform.

This role demands expert-level proficiency in Ansible for configuration management and robust automation scripting using Python.

The specialist is required to possess deep knowledge of containerization and orchestration using Docker and Kubernetes to manage microservices architecture at scale.

A foundational awareness of AI/ML concepts and exposure to OpenAI integration is a specific requirement to explore and implement next-generation automation solutions.

Primary Responsibilities :

- Design, develop, and manage complex CI/CD workflows using Azure DevOps, covering continuous integration with Azure Pipelines, managing source code in Azure Repos, and orchestrating multi-stage deployments via Azure Release Management.

- Implement and govern Infrastructure-as-Code (IaC) using Ansible to provision, configure, and manage both Azure virtual machines and container host environments with high consistency and repeatability.

- Develop advanced automation and utility scripts in Python for systems administration, cloud resource management via Azure APIs, custom monitoring integrations, and automating security compliance checks.

- Implement and maintain containerization standards using Docker, including optimizing image builds, managing private registries (e.g., Azure Container Registry), and ensuring container security hardening.

- Deploy, secure, and manage highly-available application workloads on Kubernetes (K8s) clusters (preferably Azure Kubernetes Service - AKS), utilizing Helm for package management and managing network policies and ingress controllers.

- Explore, prototype, and implement basic automation or observability enhancements by integrating and utilizing services or APIs related to OpenAI.

- Apply a basic understanding of AI/ML concepts to collaborate with data science teams, specifically in the context of MLOps, environment provisioning, and pipeline automation for model deployment.

- Ensure comprehensive monitoring, logging, and alerting are in place across the infrastructure and application stack (e.g., Prometheus, Grafana, Azure Monitor, Elastic Stack) to maintain defined Service Level Objectives (SLOs).

- Perform continuous optimization of cloud resource consumption and deployment processes to enhance efficiency and reduce overall operational expenditure on the Azure platform.

Required Technical Skills :

- DevOps : Expert-level knowledge of DevOps methodologies, Git branching strategies, and immutable infrastructure principles.

- Azure : Proven experience with core Azure services (Compute, Networking, Storage, IAM) and deep familiarity with Azure DevOps.

- Ansible : Proficiency in writing idempotent Ansible Playbooks, managing dynamic inventories, and leveraging Ansible Vault for secret management.

- Python : Advanced scripting skills for automation, data processing, and interacting with RESTful APIs; experience with Python testing frameworks.

- Docker : Expertise in Docker Compose, multi-stage builds, and troubleshooting container runtime issues.

- Kubernetes : Hands-on experience with K8s manifest creation, cluster administration, scaling strategies, and troubleshooting pod lifecycle issues.

- IaC : Working experience with Infrastructure-as-Code tools such as Terraform or Bicep for provisioning Azure resources alongside Ansible.

Preferred Skills :

- Certifications : Microsoft Certified : Azure DevOps Engineer Expert (AZ-400).

- Security : Experience with DevSecOps practices, integrating security scanning tools (e.g., SonarQube, vulnerability scanners) into the CI/CD pipeline.

- Networking : Strong understanding of Azure Virtual Networks, ExpressRoute, Load Balancers, and Application Gateways.

- Monitoring : Practical experience with advanced observability platforms (e.g., Datadog, Splunk) and custom metric integration.

- Advanced Automation : Experience with implementing OpenAI models or similar generative AI tools for tasks like code summarization, test case generation, or advanced incident analysis.

- Other Tools : Familiarity with other configuration management tools like Chef or Puppet, or advanced scripting with PowerShell/Bash.