DevOps-Engineer (AI Infrastructure)
Core
Hosting and operating highly available, scalable local AI models, services, and databases in an on-premise data center with custom GPU servers.
Role type
DevOps Engineer (AI Infrastructure)
Builds
Local AI models, services, and databases for internal use
Domain
On-premise AI infrastructure, Kubernetes, Vector databases
Deliverable
infrastructure
Required skills
Kubernetes cluster management, Containerization, CI/CD pipeline automation, Networking (Ingress/Egress), Logging and Monitoring, Application Security, Python
Preferred skills
LLMs, RAG architectures, AI Engineering (Fine-tuning, Prompt Engineering), Vector databases (PGVector, Weaviate, Qdrant), Caching (Redis)
Technologies
Kubernetes, Azure DevOps, Git, Jenkins, PGVector, Weaviate, Qdrant, Redis
Responsibilities
Manage Kubernetes clusters, Deployments, and AI components; Automate CI/CD processes; Administer and optimize vector databases with caching mechanisms.
Seniority
Mid-level, hands-on IC