Cloud Native Engineer

QuadSci is an AI product company that uses fine-tuned AI on customer data and telemetry to predict churn, contraction, and growth up to 12 months ahead for software companies. We bridge the gap between AI progress and great customer experiences, helping software companies prioritize customers to boost performance. QuadSci enables GTM leaders (Sales, Customer Success, Services, etc.) to scientifically manage the customer lifecycle, GTM performance, and ARR predictability, significantly aiding the "Rule of 40."

QuadSci is hiring a Cloud Engineer, fully remote and based in Mexico, to build and run the cloud platform behind our products. You will join a cloud infrastructure team that manages multi-cloud environments on Azure, GCP and AWS.

The role is hands-on: you will provision infrastructure, ship deployment pipelines, keep services observable and secure, and support both internal engineering teams and external customers. We work across all three clouds, so strong experience in any one of them is a solid base.

• Design, provision and maintain cloud infrastructure with Terraform, across Azure, GCP and AWS.
• Deploy and operate containerized services (for example Azure Container Apps, Kubernetes or Cloud Run), including networking, DNS, TLS and secrets.
• Build and improve CI/CD pipelines and infrastructure automation, including dependency updates and Terraform workflows.
• Run managed databases and data services such as PostgreSQL, Redis and vector databases: sizing, backups, upgrades and performance.
• Set up monitoring, logging and alerting, and take part in incident response and root-cause analysis.
• Apply identity and access management with least privilege across clouds, and manage authentication for internal and customer-facing apps.
• Support security and compliance work: evidence for audits, answers to customer security questionnaires, and hardening based on findings.
• Track and reduce cloud costs, and document architecture, runbooks and decisions for the team.
• Work with backend developers and data teams to make deployments reliable and self-service.
• Act as a trusted cloud advisor across multiple customer environments.

• Bachelor's degree (Licenciatura or Ingeniería) in Computer Science, Systems Engineering, IT or a related field, with a valid Cédula Profesional de Licenciatura issued by the SEP.
• 3+ years of hands-on experience in cloud infrastructure, DevOps or platform engineering.
• Solid experience with at least one major cloud: Azure, GCP or AWS.
• Understanding of cloud solution architecture concepts: high availability, scalability, fault tolerance, disaster recovery (RTO/RPO), network segmentation, identity and security by design, and cost-aware design, ideally guided by well-architected frameworks (Azure, AWS or Google Cloud).
• Infrastructure as Code with Terraform (or a comparable tool such as Bicep, Pulumi or CloudFormation).
• Working knowledge of Docker and container orchestration.
• Experience building CI/CD pipelines (Bitbucket Pipelines, GitHub Actions, GitLab CI, Azure DevOps or similar).
• Comfort with Linux, networking fundamentals (VNets/VPCs, DNS, load balancers, TLS) and scripting in Bash or Python.
• Professional working English, written and spoken, for daily collaboration with an international team.

• Azure knowledge or experience: Container Apps or AKS, Entra ID, Key Vault, Azure Monitor, Azure networking. An Azure certification such as AZ-104, AZ-400 or AZ-305 is a plus.
• Security and compliance: experience with audits and frameworks such as SOC 2, ISO 27001 or similar; collecting audit evidence; vulnerability management; cloud security posture tools (Microsoft Defender for Cloud, Security Command Center, AWS Security Hub).
• Backend development background: previous experience as a backend developer, having built APIs or services in Python (e.g. FastAPI), Node.js, Go, Java or C#. This role doesn't involve backend development, but that background helps you understand the applications you deploy.
• Multi-cloud experience across two or more of Azure, GCP and AWS.
• Experience with observability stacks (Elastic, Grafana, Prometheus or cloud-native tools).
• Cloud or security certifications (Azure, AWS, GCP, CKA, Security+ or similar).
• Master's degree (Maestría) in a related field.