Senior Platform Engineer AI & Observability (m/f/d)

Description: Looking for an employer you can count on? Join us! Senior Platform Engineer AI & Observability (m/f/d) Your Role and Responsibilities: Design, deploy, and operate scalable AI, observability, and cloud-native platforms based on Kubernetes and HPC technologies.

Build and optimize AI services, LLM inference platforms, and GPU-enabled workloads. Develop and maintain monitoring, logging, tracing, and security solutions using open-source technologies. Create standardized deployment workflows, automation, and platform best practices.

Enable reliable, secure, and multi-tenant operation of federated research infrastructures. Collaborate with project partners and provide technical leadership in architecture, implementation, and operations.

Your Qualifications: Required/Minimum Qualifications Master’s degree (or equivalent) in Computer Science, Data Science, Computer Engineering, or a related field. Other Requirements Experience with Linux, Docker, Kubernetes, and cloud-native technologies.

Knowledge of observability, monitoring, logging, tracing, and security concepts. Programming and scripting skills, preferably in Python, Go, or Bash. Experience with DevOps, MLOps, platform engineering, or infrastructure automation. Strong communication, collaboration, and problem-solving skills.

Excellent written and spoken English. Additional or Preferred Qualifications: Experience with AI, machine learning, LLMs, or AI-assisted operations. Hands-on experience with inference frameworks such as vLLM, Triton, Ollama, or Llama. cpp.

Experience operating GPU-accelerated, large-scale Kubernetes, or HPC environments. Knowledge of Prometheus, Grafana, Helm, GitOps, and CI/CD. Familiarity with RAG architectures, vector databases, MCP-based services, or AI agents. Experience with security monitoring tools (such as Falco or Tracee).

Experience in research projects or open-source software development. Conditions: Working time full time (40 hrs) flexible working model with electronic time