Responsibilities
- * Deploy and maintain secure cloud infrastructure primarily on GCP (Google Cloud Platform) and AWS, ensuring seamless integration between services.
- Manage and optimize GKE (Google Kubernetes Engine) clusters for high-availability AI applications and microservices.
- Infrastructure as Code: Build and enforce Terraform strategies to provision and manage infrastructure, ensuring environments are reproducible and version-controlled.
- CI/CD & Software Verification: Design and implement advanced CI/CD workflows using GitHub Actions, moving beyond simple deployments to create intelligent automation.
- Build robust verification pipelines that include automated testing, linting, security scanning, and quality gates before production release.
- Streamline the release process for backend and frontend applications, ensuring "one-click" reliability.
- Oversee the deployment, maintenance, and backup strategies for databases.
- Implement comprehensive monitoring and logging solutions (Prometheus, Grafana, Cloud Ops, Cloud Monitoring) to ensure system health, performance, and rapid incident response.
- Implement security best practices (IAM, VPC configuration, encryption) to protect sensitive AI data and intellectual property.
Qualifications*Education & Experience** B.Sc. or M.Sc. in Computer Science, Computer Engineering, or a related technical field.
* 5+ years of relevant experience in DevOps, Cloud Engineering, or Site Reliability Engineering (SRE).
* Proven experience acting as a Senior or Lead engineer, guiding architectural decisions.
*Technical Requirements** Advanced hands-on experience with GCP (specifically GKE, VPC, IAM) and a working knowledge of AWS.
* Proven ability to design and implement robust, scalable, and secure cloud architectures.
* Mastery of Docker and Kubernetes administration.
* Strong proficiency in Terraform.
* Expert knowledge of GitHub Actions for building, test, build, and deploy pipelines.
* Experience managing PostgreSQL and ClickHouse databases.
* Deep understanding of Linux System Administration.
* Experience with AI/ML lifecycle tools (e.g., Kubeflow, MLflow, Vertex AI).
* Strong proficiency in Python and Bash scripting.
* Familiarity with DevSecOps tools and practices.
* Bonus: Official GCP Certifications (e.g., Professional Cloud Architect, Professional Cloud DevOps Engineer) and Kubernetes Certifications (e.g., CKA, CKAD, CKS) are highly preferred.
* Bonus: Knowledge of Javascript/Node.js is a strong plus.
*Soft Skills & Mindset** Ability to design long-term solutions rather than quick fixes.
* Excellent ability to explain complex cloud concepts to Data Scientists and business stakeholders.
* Comfortable working in a fast-paced environment with evolving requirements.
* Fluent English is a must.