We are seeking a highly skilled and experienced DevOps Team Lead to join our dynamic team.
As the DevOps Team Lead, you will be responsible for leading and managing a global team of DevOps engineers, driving our cloud-native infrastructure, and ensuring the reliability, scalability, and security of our production environments.
Key Responsibilities:
Lead and manage a global team of 5 DevOps engineers, fostering collaboration, mentorship, and professional growth
Design, implement, and optimize cloud-native architectures using AWS services
Manage and scale our Kubernetes (K8S) clusters to support our microservices architecture
Drive the implementation of CI/CD pipelines and infrastructure-as-code practices
Ensure high availability, performance, and security of our production environments
Collaborate with development, product, and security teams to align DevOps practices with business goals
Continuously improve our DevOps processes, tools, and methodologies.
Requirements: At least 3+ years of experience leading and managing a global DevOps team
At least 5+ years of hands-on DevOps experience in production environments
At least 5+ years of experience with AWS services (EC2, EKS, S3, RDS, SCP etc.)
Proven experience in High scale production environment
Expert knowledge of Kubernetes (K8S) and container orchestration, including completion tools
Strong scripting skills (Python, Bash, etc.) and experience with infrastructure-as-code (Terraform, CloudFormation)
Experience with CI/CD tools (Jenkins, GitLab CI, etc.) and version control systems (Git)
Familiarity with monitoring and logging tools (Prometheus, Grafana, ELK stack, APM monitoring)
AWS certifications (Solutions Architect, DevOps Engineer)
Experience with serverless architectures (AWS Lambda, API Gateway)
Knowledge of security best practices and compliance frameworks (ISO 27001, SOC 2)
Experience with GitOps methodologies and tools (ArgoCD, Helm, admission control)
Experience in any of the following is a strong plus:
Leveraging AI tools to improve DevOps workflows, observability, and engineering productivity
Building self-service capabilities and internal developer platforms
Designing and implementing workflows involving AI agents, including automation, monitoring, and incident response use cases.
This position is open to all candidates.