Devops Expert

Job Summary:

We are seeking a Senior DevOps Cloud Engineering Specialist with extensive experience in cloud infrastructure, DevOps practices, CI/CD pipelines, engineering methodologies, containerization, and virtualization technologies.

This role goes beyond traditional cloud engineering and requires a strong capability to design and enable scalable, cloud-based ecosystems that support development, testing, simulation, and validation across diverse engineering domains. The candidate will act as a key enabler for digital transformation, driving standardization, automation, and adoption of modern tools and practices.

Key Responsibilities:

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• 12+ years of strong hands-on experience in Cloud Engineering, DevOps, or Platform Engineering roles.
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• Architect and manage scalable, secure, and flexible cloud platforms (Azure/AWS/GCP) to support multi-domain engineering needs.
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• Design and implement cloud-based CI/CD pipelines integrating development, testing, and validation workflows.
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• Enable end-to-end automation across build, test, verification, validation, and deployment processes.
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• Define and standardize engineering processes, methods, and toolchains across teams.
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• Establish cloud-based Verification & Validation (V&V) frameworks, including test automation, simulation, and traceability.
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• Lead virtualization and containerization strategies to enable reproducible and scalable environments.
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• Integrate diverse tools (ALM, DevOps, testing, simulation) into unified cloud-based ecosystems.
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• Ensure best practices in cloud security, compliance, cost optimization, and observability.
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• Support digital engineering initiatives such as model-based development and virtual validation environments.
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• Provide technical leadership, mentoring, and guidance across teams and domains.
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• Continuously evaluate and adopt emerging cloud technologies and tools.
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Required Skills:

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• Strong expertise in at least one major cloud platform (Azure, AWS, or GCP). Should be able to work on any similar company specific platform.
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• Mandatory Experience in large-scale or multi-tenant cloud environments.
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• Proven experience in designing CI/CD pipelines and DevOps workflows.
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• Strong understanding of engineering processes, methods, and toolchain integration.
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• Experience in Verification & Validation (V&V), including test automation and validation strategies.
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• Proficiency in scripting and automation (Python, Bash, PowerShell).
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• Hands-on experience with containerization and virtualization technologies.
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• Solid understanding of Linux/Unix environments and system troubleshooting.
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• Strong problem-solving and cross-domain collaboration skills.
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Preferred Skills:

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• Familiarity with standards such as ISO 26262, ASPICE
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• Exposure to AI/ML tools for automation, testing, or operations (AIOps).
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Tools & Technologies (Expected Exposure):

Cloud Platforms:

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• Microsoft Azure, AWS, Google Cloud Platform
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CI/CD & DevOps:

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• GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps
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Infrastructure as Code & Automation:

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• Terraform, Pulumi, Bicep, ARM Templates, AWS CloudFormation
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• Ansible, Chef
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Containerization & Orchestration:

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• Docker, Kubernetes (AKS, EKS, GKE), OpenShift
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Virtualization & Environment Management:

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• VMware, Hyper-V, VirtualBox, KVM
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• Vagrant
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Verification & Validation / Testing:

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• Selenium, Cypress, Playwright
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• Robot Framework, pytest, JUnit
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• Postman, REST Assured
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• MATLAB/Simulink (for simulation use cases)
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• dSPACE, Vector tools (CANoe/CANalyzer) – where applicable
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Observability & Monitoring:

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• Prometheus, Grafana, ELK Stack, Loki
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• Azure Monitor, AWS CloudWatch, GCP Operations Suite
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Security & DevSecOps:

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• HashiCorp Vault, Azure Key Vault, AWS Secrets Manager
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• Snyk, Trivy, SonarQube, OWASP ZAP
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Collaboration & ALM Tools:

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• Jira, Confluence, Polarion, Azure Boards
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• Git (GitHub, GitLab, Bitbucket)
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Emerging & Advanced:

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• AI-assisted DevOps tools (GitHub Copilot, Azure AI, Vertex AI)
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• Cloud-based simulation tools
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