Lead the design and management of scalable cloud infrastructure, Kubernetes deployments, CI/CD pipelines, observability, DevSecOps practices, team mentoring, and AI/ML workflows at GlobalData PLC.

Job Description – Principal Devops Engineer

Experience Level: 7 to 10+ years Location: [Bangalore]

Key Responsibilities

• Design and manage scalable, secure, and cost-optimized cloud infrastructure (AWS/GCP/Azure).
• Lead Kubernetes (multi-cluster) deployments and implement Infrastructure as Code (Terraform/Helm).
• Build and optimize CI/CD pipelines (Jenkins, GitLab, GitHub Actions) with GitOps practices.
• Ensure observability with Prometheus, Grafana, ELK, and lead incident management.
• Drive DevSecOps—security automation, IAM, and vulnerability management.
• Mentor DevOps/SRE team, foster automation culture, and align with AI product goals.
• Enable AI/ML workflows (MLOps) for model deployment, monitoring, and lifecycle management.

Key Qualifications

• 7–12 years in DevOps/SRE/Platform Engineering, with startup or AI/ML experience preferred.
• Strong expertise in Kubernetes, IaC (Terraform, Helm), and cloud platforms (AWS/GCP/Azure).
• Proficiency in automation/scripting (Python, Go, Bash) and modern CI/CD practices.
• Experience with observability tools (Prometheus, Grafana, ELK, NewRelic) and reliability engineering.
• Knowledge of DevSecOps principles, IAM, RBAC, and cloud security.
• Proven leadership in mentoring teams, cross-functional collaboration, and scaling systems.
• Exposure to MLOps workflows (model CI/CD, monitoring, reproducibility) and GPU workloads.

• 7–12 years in DevOps/SRE/Platform Engineering, with startup or AI/ML experience preferred.
• Strong expertise in Kubernetes, IaC (Terraform, Helm), and cloud platforms (AWS/GCP/Azure).
• Proficiency in automation/scripting (Python, Go, Bash) and modern CI/CD practices.
• Experience with observability tools (Prometheus, Grafana, ELK, NewRelic) and reliability engineering.
• Knowledge of DevSecOps principles, IAM, RBAC, and cloud security.
• Proven leadership in mentoring teams, cross-functional collaboration, and scaling systems.
• Exposure to MLOps workflows (model CI/CD, monitoring, reproducibility) and GPU workloads.

Benefits information is not provided in the job posting.