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Senior DevOps Engineer

webAI

Join our team as a Senior DevOps Engineer, where you will design, build, and scale secure infrastructure supporting AI workloads across cloud and edge environments. This high-impact individual contributor role will involve driving infrastructure architecture, platform reliability, and security best practices across the organization. You will work closely with engineering teams to implement scalable, automated infrastructure solutions that enable our AI platform to operate efficiently in diverse deployment scenarios.

Design, build, and scale secure infrastructure supporting AI workloads across cloud and edge environments.

Develop secure CI/CD pipelines with integrated security controls and support MLOps infrastructure initiatives including model deployment automation.

Responsibilities

  • Implement scalable, automated infrastructure solutions that enable the AI platform to operate efficiently across diverse deployment scenarios.

Requirements

  • This role requires strong technical depth, production experience, and the ability to translate complex requirements into resilient infrastructure systems
  • 5–8+ years of experience in DevOps, Site Reliability Engineering, or Infrastructure Engineering supporting production systems
  • Strong understanding of cloud security best practices and access management
  • Strong expertise with Docker, Kubernetes, and cloud-native architectures
  • Experience working with AWS, Azure, or GCP including compute, networking, and managed services
  • 3–5+ years of hands-on experience implementing Infrastructure as Code (Terraform, Pulumi, Ansible)
  • Proven experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, ArgoCD)
  • Experience implementing monitoring and observability in production environments
  • Programming experience in Python (preferred), Go, or Bash for automation
  • Strong communication skills and ability to collaborate cross-functionally
  • Exposure to multi-cloud or hybrid cloud environments
  • Experience supporting AI/ML or MLOps workflows
  • Understanding of cost optimization and cloud efficiency practices

Preferred

  • Experience with edge computing or distributed systems
  • Familiarity with service mesh technologies (Istio, Linkerd)
  • Relevant certifications (CKA, AWS Solutions Architect, Terraform Associate, etc.)