Mid/Senior DevOps Cloud Engineer
Position Type: Remote (Egypt)
About Intelmatix
Intelmatix is a pioneering deep-tech AI company founded by MIT technologists, with a global presence in Riyadh, London, and Boston. We are on a mission to transform businesses into cognitive enterprises through Decision Intelligence. Our technology blends cutting-edge AI with real-world applications, delivering scalable, secure, and data-driven solutions to global clients.
Role Overview
We are looking for a highly motivated Mid/Senior DevOps Cloud Engineer with a specialized focus on Google Cloud Platform (GCP) to join our Platform Engineering team. You will play a critical part in architecting, shaping, and supporting the infrastructure that powers our AI-driven platforms.
This role is ideal for a GCP expert who thrives on infrastructure automation, cloud-native solutions, and enabling the seamless deployment of complex applications, including AI/ML models. While GCP is our primary focus for this role, exposure to AWS and Azure is a significant plus as we navigate multi-cloud environments.
Key Responsibilities
- GCP Infrastructure Management: Architect, maintain, and optimize cloud infrastructure on GCP with a focus on reliability, scalability, and cost-efficiency.
- Infrastructure as Code (IaC): Automate global infrastructure provisioning using Terraform to ensure consistent environments across the lifecycle.
- CI/CD Orchestration: Build and maintain robust CI/CD pipelines for application, data, and model deployment workflows (GitHub Actions).
- AI/ML Collaboration: Work closely with Data Science teams to deploy and monitor machine learning models and analytical services.
- Security & Networking: Implement and enforce security best practices, including IAM, VPC service controls, and Zero Trust architectures.
- Observability: Set up and maintain modern observability stacks (Prometheus, Grafana, Loki) for proactive monitoring and alerting.
- Hybrid/Multi-Cloud Strategy: Assist in managing cross-cloud integrations, leveraging your knowledge of AWS and Azure where applicable.
Required Qualifications
- Education: Bachelor’s degree in Computer Science, Engineering, or a related field.
- Experience: 3–5 years of dedicated experience in DevOps, Site Reliability Engineering (SRE), or Cloud Engineering roles.
- GCP Expertise (Must-Have): Deep hands-on experience with Google Cloud services (e.g., GCE, GKE, GCS, Cloud SQL, IAM, and VPC).
- Containerization: Strong proficiency with Docker and orchestration via Google Kubernetes Engine (GKE) or similar services in other cloud prroviders.
- IaC Mastery: Proven experience managing infrastructure through Terraform.
- CI/CD: Experience building automation pipelines using GitHub Actions or similar tools.
- Scripting: Proficiency in Python and Bash for task automation and tooling.
- Linux Systems: Solid understanding of Linux system administration and performance tuning.
Preferred Qualifications
- Certifications: Google Professional Cloud DevOps Engineer or Professional Cloud Architect or any cloud certifications for other cloud providers.
- Multi-Cloud: Familiarity with AWS (EC2, S3, EKS) or Azure (AKS, App Service) is highly desirable.
- Data/MLOps: Familiarity with GCP-specific data tools (BigQuery, Vertex AI, Dataflow) or MLOps tools (MLflow, Airflow).
- Edge Security: Understanding of Zero Trust Network (ZTN) concepts and Cloudflare.
- Database Admin: Basic experience with PostgreSQL administration.
- Startup Mindset: Experience working in fast-paced, agile, deep-tech environments.
Tech Stack
- Primary Cloud: GCP (GKE, GCE, BigQuery).
- Secondary Clouds: AWS, Azure, OCI.
- IaC: Terraform, Terragrunt.
- CI/CD: GitHub Actions.
- Security: Cloudflare (ZTN).
- Monitoring: Prometheus Stack (Prometheus, Grafana, Loki).
- Application: Kong (API Gateway), Java Spring Boot, Python, Go.
- Data: GCP Dataflow, BigQuery, PostgreSQL.
Why Join Us?
At Intelmatix, you’ll work on impactful technology alongside a global team of top-tier professionals. We offer the autonomy to innovate, the resources to grow, and the opportunity to shape the future of AI-enabled decision-making across industries.