Senior DevOps Engineer

Accountabilities: Design, build, and maintain scalable cloud infrastructure across AWS, Google Cloud Platform, and Azure environments. Develop and optimize CI/CD pipelines to enable efficient code integration, testing, and automated deployments. Implement Infrastructure as Code practices using tools such as Terraform to ensure consistency, repeatability, and scalability. Containerize applications and manage orchestration platforms using Docker and Kubernetes. Build and operate monitoring, logging, observability, and alerting frameworks to ensure high availability and proactive issue resolution. Manage secure, private, and VPC-isolated enterprise deployments with strong emphasis on security, compliance, and audit readiness. Collaborate with machine learning teams to deploy and scale AI training and inference workloads, including GPU-enabled infrastructure when required. Partner with engineering and security stakeholders to improve infrastructure resilience, operational processes, and cloud cost efficiency. Maintain technical documentation and establish best practices for infrastructure operations and platform management. Requirements Minimum of 3 years of experience in DevOps, Cloud Infrastructure, Site Reliability Engineering, or related disciplines. Strong hands-on expertise with at least one major cloud platform, including AWS, GCP, and/or Microsoft Azure. Solid experience with containerization and orchestration technologies such as Docker and Kubernetes. Proven ability to design and manage CI/CD pipelines using GitHub Actions or similar automation tools. Practical experience with Infrastructure as Code frameworks, particularly Terraform. Strong understanding of networking concepts, including VPCs, cloud security groups, and cloud-native services. Experience managing production-grade environments with a focus on scalability, reliability, security, and performance optimization. Knowledge of monitoring, logging, and observability platforms and best practices. Familiarity with GPU infrastructure and machine learning workload deployment is considered a strong advantage. Excellent troubleshooting, analytical thinking, and problem-solving capabilities. Strong communication skills in English, with the ability to collaborate effectively across distributed teams. Benefits Fully remote opportunity offering flexibility and work-life balance. Opportunity to work on cutting-edge AI and enterprise technology solutions. Exposure to multi-cloud architectures and advanced DevOps practices. Collaborative and high-growth environment with significant ownership and autonomy. Opportunity to work closely with engineering, security, and AI teams on impactful projects. Fast-paced startup culture that encourages innovation, continuous learning, and professional development. Participation in building scalable infrastructure supporting next-generation AI applications. Structured interview process with direct exposure to technical and leadership stakeholders.