Lead Cloud Infrastructure Engineer
inventurus knowledge solnRepublic Of India, IN19 days ago
Job description10+ years of experience in DevOps, Cloud Engineering, or related fields. Deep hands-on experience with Google Cloud Platform (GKE, Cloud Run, Cloud Build, IAM, VPC, Cloud Storage, Pub / Sub, BigQuery). Expertise in CI / CD pipeline design and maintenance for both application and ML workflows. Strong experience with Docker and Kubernetes, preferably GKE. Solid understanding of MLOps practices and tools (Kubeflow, Vertex AI, MLflow). Working knowledge of DevSecOps tools and practices : static / dynamic analysis, security scanning, secret management (e.G., HashiCorp Vault, GCP Secret Manager). Experience with DataOps frameworks and orchestration tools (e.G., Airflow, dbt, Dataflow, Cloud Composer). Proficient in IaC tools (Terraform, Ansible, Deployment Manager). Familiar with GitOps and tools like ArgoCD, FluxCD. Strong scripting and automation skills (Python, Bash, YAML). Deep understanding of modern software development lifecycles and cloud-native design patterns. GCP Certifications (e.G., Professional Cloud DevOps Engineer , Professional Cloud Architect ). Experience with hybrid cloud or multi-cloud environments. Knowledge of service mesh and API gateways (e.G., Istio, Envoy). Experience with cost optimization, cloud budgeting, and FinOps strategies. Familiarity with compliance frameworks like HIPAA, SOC 2, or ISO 27001.
About the Role :
We are seeking a highly experienced and hands-on DevOps Subject Matter Expert (SME) with deep specialization in Google Cloud Platform (GCP) and a proven track record in designing and implementing CI / CD pipelines, cloud-native architectures, MLOps frameworks, and DevSecOps practices . The ideal candidate will bring a strong foundation in cloud infrastructure, container orchestration, automation, and secure software delivery , playing a strategic and technical leadership role across projects.
Key Responsibilities :
- Design, implement, and optimize CI / CD pipelines using tools like Cloud Build, GitHub Actions, Jenkins, ArgoCD, Spinnaker , etc.
- Define and maintain cloud deployment architectures on GCP, ensuring scalability, availability, and security.
- Lead MLOps practices by integrating model development, testing, deployment, and monitoring using Vertex AI, Kubeflow, MLflow, etc.
- Implement DevSecOps best practices, including IaC security scanning, secrets management, container image scanning, and policy enforcement.
- Architect and manage DataOps pipelines for data ingestion, transformation, and validation across environments.
- Drive containerization efforts using Docker , Kubernetes (GKE), Helm, and service mesh technologies (Istio, Linkerd).
- Implement infrastructure as code (IaC) using Terraform , Deployment Manager , or Pulumi .
- Collaborate with development, data science, and QA teams to ensure seamless integration of DevOps processes throughout the SDLC.
- Monitor system performance, cost optimization, and operational SLAs using GCP-native tools (Cloud Monitoring, Cloud Logging) and third-party observability tools (Datadog, Prometheus, Grafana).
- Guide the adoption of GitOps, automated testing, release management, and rollback strategies in fast-paced cloud-native environments.
Required Qualifications :
Preferred Qualifications :
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Cloud Infrastructure Engineer • Republic Of India, IN
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