Design and implement secure, scalable infrastructure across multi-cloud (AWS, Azure, GCP), hybrid, and edge environments
Build and maintain Infrastructure as Code (Terraform, Pulumi, Ansible) using GitOps workflows and automated validation
Deploy and operate Kubernetes clusters optimized for AI/ML workloads, including GPU scheduling and container security best practices
Develop secure CI/CD pipelines with integrated security controls (SAST, DAST, vulnerability scanning, secrets management)
Support MLOps infrastructure initiatives including model deployment automation, versioning, and lifecycle management
Implement observability and monitoring frameworks using tools such as Prometheus, Grafana, ELK, or Datadog
Enforce security best practices including IAM, encryption, network segmentation, and compliance automation
Participate in incident response, reliability improvements, postmortems, and disaster recovery planning
Develop reusable infrastructure modules and documentation (runbooks, architecture docs, standards)
Mentor junior and mid-level engineers on DevOps best practices and infrastructure design

5–8+ years of experience in DevOps, Site Reliability Engineering, or Infrastructure Engineering supporting production systems
Strong expertise with Docker, Kubernetes, and cloud-native architectures
3–5+ years of hands-on experience implementing Infrastructure as Code (Terraform, Pulumi, Ansible)
Experience working with AWS, Azure, or GCP including compute, networking, and managed services
Proven experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, ArgoCD)
Programming experience in Python (preferred), Go, or Bash for automation
Experience implementing monitoring and observability in production environments
Strong understanding of cloud security best practices and access management
Strong communication skills and ability to collaborate cross-functionally

webAI™

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