We are looking for a Senior DevOps Engineer to help build, scale, and operate the cloud infrastructure behind our AI-powered platform. You will work closely with software engineers, data engineers, and AI teams to ensure our infrastructure is reliable, secure, scalable, and highly automated. This role is ideal for someone who enjoys solving complex infrastructure challenges and building modern cloud-native environments.

Responsibilities

Design, build, and maintain scalable cloud infrastructure. Manage and optimize AWS environments. Develop and maintain Infrastructure as Code using Terraform. Build and improve CI/CD pipelines for multiple engineering teams. Automate deployment, provisioning, and operational processes. Support containerized workloads and cloud-native applications. Monitor system health, performance, and reliability. Improve observability through monitoring, logging, and alerting solutions. Implement security best practices across infrastructure and deployment pipelines. Troubleshoot production issues and participate in root-cause analysis. Collaborate with engineering and data teams to support AI and analytics workloads. Contribute to infrastructure architecture and platform evolution. Requirements 5+ years of experience in DevOps, Cloud Engineering, or Infrastructure Engineering. Strong hands-on AWS experience. Solid experience with Terraform and Infrastructure as Code. Strong Linux administration skills. Experience with Docker and containerized environments. Experience building and maintaining CI/CD pipelines. Experience with GitHub Actions, GitLab CI, Jenkins, CircleCI, or similar tools. Strong scripting skills using Python, Bash, or similar languages. Experience with monitoring and observability tools such as Prometheus, Grafana, ELK, CloudWatch, or similar. Good understanding of networking, security, VPNs, firewalls, and load balancing. Experience supporting production systems in cloud environments. Strong troubleshooting and problem-solving skills. Fluent English communication skills.

Nice to Have

Kubernetes experience. Experience supporting AI, machine learning, or data analytics platforms. Experience with Azure or GCP. Experience with security and compliance tooling. Experience in SaaS or high-scale data platforms. Previous exposure to SRE practices and reliability engineering.