Senior Infrastructure Engineer

Beschreibung

Job Zusammenfassung In dieser Rolle entwirfst du skalierbare und sichere Infrastrukturen für KI- und ML-Anwendungen auf AWS, verwaltest Container und CI/CD-Pipelines und optimierst Datenverfügbarkeit und -sicherheit. Job Zusammenfassung In dieser Rolle entwirfst du skalierbare und sichere Infrastrukturen für KI- und ML-Anwendungen auf AWS, verwaltest Container und CI/CD-Pipelines und optimierst Datenverfügbarkeit und -sicherheit. Deine Rolle im Team Design, deploy, and maintain scalable and secure infrastructure supporting AI and ML workloads. Build and maintain AWS cloud environments for compute (EC2, ECS/EKS, Lambda), storage (S3, EFS, FSx), and networking (VPC, Transit Gateway, PrivateLink, Route 53, load balancers). Implement security best practices using IAM, KMS, Secrets Manager, GuardDuty, and Security Hub. Support and optimize AI/ML workloads across AWS services (SageMaker, Bedrock, Batch, Step Functions). Develop and maintain Infrastructure as Code (IaC) using Terraform, AWS CDK, and CloudFormation. Manage containerized workloads and orchestration platforms (Docker, EKS, Fargate), including GPU scheduling and scaling. Set up and maintain monitoring and observability frameworks using CloudWatch and OpenTelemetry. Build and manage CI/CD pipelines (CircleCI, GitHub Actions, GitLab CI) for infrastructure automation and ML/Gen AI deployments. Collaborate with ML and Generative AI teams to scale models, optimize performance, and design efficient prompt or inference pipelines. Develop runbooks and SOPs for AI service deployment, troubleshooting, and performance optimization. Ensure security, compliance, and data protection across AI datasets and environments. Unsere Erwartungen an dich Ausbildung A Master's degree in Machine Learning, Computer Science with a preference for specialization in the NLP domain. Qualifikationen Strong proficiency in Linux administration and systems-level troubleshooting. Proficiency in container orchestration (Kubernetes/EKS) and infrastructure automation tools. Familiarity with monitoring, logging, and observability stacks (Prometheus, Grafana, OpenTelemetry). Understanding of AI/ML concepts, including model deployment, inference scaling, and LLM performance tuning. Working knowledge of security best practices, IAM roles, encryption, and compliance controls. Excellent collaboration and communication skills to partner with ML engineers, data scientists, and product teams. Erfahrung Deep expertise in AWS cloud services, with experience in compute, storage, networking, and security domains. Hands-on experience with IaC tools such as Terraform, AWS CDK, or CloudFormation. Experience implementing CI/CD pipelines for automated deployment and testing. Themen mit denen du dich im Job beschäftigst Machine Learning AI Metadaten Level: Senior Job Feld: IT, Data, DevOps Anstellung: Vollzeit Vertragsart: Unbefristetes Dienstverhältnis Arbeitsmodell: Onsite Unternehmenstyp: Etablierte Firma Branche: Internet, IT, Telekom Ort: München | Deutschland

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