Senior DevOps Engineer (Cloud-Native, AI-Driven Platform)

• 5+ years of experience in DevOps / Cloud Engineering roles.
• Strong hands-on experience with AWS or Azure — experience with both is a strong plus.
• Deep understanding of containerization and distributed systems, with production experience in Kubernetes (required).
• Proven experience building and maintaining CI/CD pipelines (Jenkins, GitHub Actions, Bitbucket Pipelines, GitLab CI or similar).
• Experience implementing Infrastructure as Code.
• Hands-on experience with Microsoft SQL Server (administration, performance tuning, backup/restore, high availability).
• Experience with Redis in production (caching, session storage, pub/sub).
• Strong knowledge of networking, security, and system architecture.
• Experience working in high-availability SaaS environments.
• Solid understanding of observability, monitoring, and incident management, including Grafana dashboards and alerting.
• Automation-first mindset.
• Experience collaborating with backend engineering teams.
• Languages: fluent Spanish and professional English (both required).

We don’t expect you to master every tool listed above, but we do expect solid hands-on experience with at least one technology in each area: cloud provider (AWS / Azure), containers & orchestration, CI/CD, Infrastructure as Code, observability, and databases & caching.

• Experience implementing DevSecOps practices.
• Familiarity with AI/ML infrastructure requirements.
• Experience with cost optimization strategies in cloud environments.
• Knowledge of GitOps workflows.
• Experience in multi-tenant SaaS platforms.
• Hands-on experience with both AWS and Azure.
• Scripting skills (Bash, Python).
• French — a huge plus (we can dream!).

• High ownership and architectural impact.
• Cloud-native SaaS platform with real scale challenges.
• Opportunity to shape infrastructure evolution toward AI-native capabilities.
• Cross-functional, product-driven engineering culture.
• International environment with technical autonomy.

We are building the next generation of AI-native software for the hospitality industry. Our platform powers complex, multi-tenant environments across multiple companies and product lines, operating in high-availability, high-performance scenarios.

Our systems handle critical operational workflows where uptime, scalability, and security are non-negotiable. As we evolve toward AI-native capabilities and intelligent automation, our infrastructure must be resilient, observable, and ready to scale dynamically.

We believe DevOps is not a support function — it is a core engineering discipline that enables product velocity, reliability, and innovation.

If you enjoy designing robust infrastructure, automating everything, and building platforms that engineers love to use, we’d love to meet you.

• Build the Platform Behind the Platform: Design and evolve the cloud infrastructure that powers our multi-tenant SaaS ecosystem.
• Enable Engineering Velocity: Improve CI/CD pipelines, developer experience, and deployment automation.
• Drive Reliability & Observability: Ensure high availability, performance, and real-time visibility across distributed systems.
• Architect for Scale: Design infrastructure that supports growth, AI workloads, and distributed services.
• Champion Infrastructure as Code: Everything reproducible, versioned, and automated.
• Embed Security by Design: Implement DevSecOps best practices across the delivery lifecycle.
• Design, implement, and maintain cloud infrastructure in AWS and/or Azure.
• Manage and optimize containerized workloads using Docker and Kubernetes.
• Build and evolve CI/CD pipelines (Jenkins, GitHub Actions, Bitbucket Pipelines, GitLab CI or equivalent).
• Implement Infrastructure as Code (Terraform or similar).
• Ensure high availability, disaster recovery, and backup strategies.
• Improve monitoring, logging, and alerting systems (ELK stack, Grafana dashboards and alerting, Azure Monitor / Log Analytics, Amazon CloudWatch and other observability tools).
• Operate, monitor, and tune Microsoft SQL Server databases (performance, backups, high availability).
• Optimize system performance, scalability, and cost efficiency.
• Collaborate closely with backend engineers (Java / Kotlin, C#, Node.js) to improve deployment patterns and runtime reliability.
• Automate operational processes and reduce manual intervention.
• Leverage AI-assisted tooling (Claude, Codex, automation agents, anomaly detection systems) to improve operational efficiency.
• Participate in architectural discussions to ensure infrastructure scalability and resilience.

You don’t just maintain infrastructure — you engineer the reliability of the business.

Cloud Building Blocks: AWS & Azure

We run workloads on both AWS and Azure. We are looking for solid hands-on experience with IaaS and core managed cloud services on at least one of them — knowing the equivalent on the other cloud is a strong plus. These are the building blocks you’ll work with:

• Virtual machines & autoscaling — Azure: Azure Virtual Machines, VM Scale Sets | AWS: Amazon EC2, Auto Scaling Groups
• Virtual networking — Azure: VNet, NSGs, VNet Integration, Private Endpoints | AWS: VPC, Security Groups, PrivateLink
• L7 load balancing + WAF — Azure: Application Gateway + WAF | AWS: Application Load Balancer + AWS WAF
• Web app / API hosting — Azure: App Service | AWS: Elastic Beanstalk / App Runner
• Managed Kubernetes — Azure: AKS | AWS: EKS
• Message queues — Azure: Azure Storage — Queues | AWS: Amazon SQS
• Object storage — Azure: Azure Storage — Blobs | AWS: Amazon S3
• In-memory cache — Azure: Azure Cache for Redis | AWS: Amazon ElastiCache (Redis / Valkey)
• Managed SQL Server — Azure: Azure SQL / SQL Managed Instance | AWS: Amazon RDS for SQL Server
• Workload identity (secretless auth) — Azure: Managed Identity + DefaultAzureCredential | AWS: IAM Roles (instance profiles, IRSA) + SDK default credential chain
• Secrets & keys — Azure: Key Vault | AWS: AWS Secrets Manager / KMS
• Transactional email — Azure: Azure Communication Services (Email) | AWS: Amazon SES
• Per-environment configuration — Azure: App Settings | AWS: Systems Manager Parameter Store / AppConfig
• Logs, metrics & alerts — Azure: Log Analytics / Azure Monitor | AWS: Amazon CloudWatch
• Runtime diagnostics — Azure: Kudu / App Service diagnostics | AWS: CloudWatch Logs Insights / SSM Session Manager