Senior Cloud Engineer
Location: Gurugram (Hybrid – Local to NCR Preferred)
Employment Type: Full-Time
Interview Mode: Virtual
Notice Period: Immediate to 15 Days
Job Description
We are seeking a skilled Senior Cloud Engineer to design, deploy, and maintain secure, scalable cloud infrastructure supporting data, AI, and DevOps operations. The ideal candidate will have hands‑on experience with Terraform, Google Cloud Platform (GCP), and modern CI/CD practices.
Key Responsibilities
- Design, deploy, and maintain cloud infrastructure using Terraform and GCP best practices.
- Architect, implement, and manage network configurations, including secure setups for platforms like Workbench.
- Develop and manage new project architectures, ensuring high availability, scalability, and cost efficiency.
- Support and optimize Vertex AI applications, including pipeline automation, resource management, and integration with other GCP services.
- Collaborate with cross-functional teams to deliver end-to-end cloud solutions aligned with business goals.
- Implement and maintain CI/CD pipelines to support rapid and reliable application delivery.
- Monitor, troubleshoot, and optimize cloud environments for performance, reliability, and security.
- Drive DevOps operations, enhancing deployment automation and infrastructure resilience.
- Maintain up-to-date documentation of infrastructure and operational procedures.
- Good understanding of Data Product development.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field.
- Proven experience with Terraform and Infrastructure-as-Code (IaC) principles.
- Strong understanding of GCP services including Compute Engine, VPC, Cloud Storage, Vertex AI, Cloud Build, etc.
- Experience with network architecture and security configuration in GCP.
- Practical knowledge of CI/CD tools such as Jenkins, GitLab CI, or similar.
- Familiarity with containerization technologies like Docker and Kubernetes is a plus.
- Excellent problem‑solving and collaboration skills.
Preferred Experience
- Google Cloud Professional Cloud Engineer certification or equivalent with 7+ years of experience.
- Prior experience building AI/ML pipelines and MLOps workflows.
- Strong background in scripting languages such as Python and Bash.