Senior DevOps Engineer Cloud-Native Ai-Driven Platform H/F

How You'll Have Impact

• 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.

What You'll Do

• 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