Job Summary:
We are seeking a Senior Cloud Engineering Expert with the ability to operate across domains, including engineering processes, methods, toolchains, verification & validation (V&V), and virtualization.
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:
- Architect and manage scalable, secure, and flexible cloud platforms (Azure/AWS/GCP) to support multi-domain engineering needs.
- Design and implement cloud-based CI/CD pipelines integrating development, testing, and validation workflows.
- Enable end-to-end automation across build, test, verification, validation, and deployment processes.
- Define and standardize engineering processes, methods, and toolchains across teams.
- Establish cloud-based Verification & Validation (V&V) frameworks, including test automation, simulation, and traceability.
- Lead virtualization and containerization strategies to enable reproducible and scalable environments.
- Integrate diverse tools (ALM, DevOps, testing, simulation) into unified cloud-based ecosystems.
- Ensure best practices in cloud security, compliance, cost optimization, and observability.
- Support digital engineering initiatives such as model-based development and virtual validation environments.
- Provide technical leadership, mentoring, and guidance across teams and domains.
- Continuously evaluate and adopt emerging cloud technologies and tools.
Required Skills:
- 6–10 years of strong hands-on experience in Cloud Engineering, DevOps, or Platform Engineering roles.
- Strong expertise in at least one major cloud platform (Azure, AWS, or GCP). Should be able to work on any similar company specific platform.
- Mandatory Experience in large-scale or multi-tenant cloud environments.
- Proven experience in designing CI/CD pipelines and DevOps workflows.
- Strong understanding of engineering processes, methods, and toolchain integration.
- Experience in Verification & Validation (V&V), including test automation and validation strategies.
- Proficiency in scripting and automation (Python, Bash, PowerShell).
- Hands-on experience with containerization and virtualization technologies.
- Solid understanding of Linux/Unix environments and system troubleshooting.
- Strong problem-solving and cross-domain collaboration skills.
Preferred Skills:
- Familiarity with standards such as ISO 26262, ASPICE
- Exposure to AI/ML tools for automation, testing, or operations (AIOps).
Tools & Technologies (Expected Exposure):
Cloud Platforms:
- Microsoft Azure, AWS, Google Cloud Platform
CI/CD & DevOps:
- GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps
Infrastructure as Code & Automation:
- Terraform, Pulumi, Bicep, ARM Templates, AWS CloudFormation
- Ansible, Chef
Containerization & Orchestration:
- Docker, Kubernetes (AKS, EKS, GKE), OpenShift
Virtualization & Environment Management:
- VMware, Hyper-V, VirtualBox, KVM
- Vagrant
Verification & Validation / Testing:
- Selenium, Cypress, Playwright
- Robot Framework, pytest, JUnit
- Postman, REST Assured
- MATLAB/Simulink (for simulation use cases)
- dSPACE, Vector tools (CANoe/CANalyzer) – where applicable
Observability & Monitoring:
- Prometheus, Grafana, ELK Stack, Loki
- Azure Monitor, AWS CloudWatch, GCP Operations Suite
Security & DevSecOps:
- HashiCorp Vault, Azure Key Vault, AWS Secrets Manager
- Snyk, Trivy, SonarQube, OWASP ZAP
Collaboration & ALM Tools:
- Jira, Confluence, Polarion, Azure Boards
- Git (GitHub, GitLab, Bitbucket)
Emerging & Advanced:
- AI-assisted DevOps tools (GitHub Copilot, Azure AI, Vertex AI)
- Cloud-based simulation tools