testKI-Engineer*in (all genders) - LLM-Infrastruktur und KI-Plattform
Tasks
- Advise research teams on feasibility
- Apply prompt engineering best practices
- Build LLMOps pipelines
- Build knowledge via workshops onboarding and documentation
- Configure coding agent tools
- Create embeddings and vector representations
- Ensure reliable operation of local RAG systems
- Establish monitoring and observability
- Evaluate and benchmark LLMs
- Implement access control and authentication
- Implement prompt injection protection
- Manage logging availability and incident handling
- Manage vector databases
- Monitor market and new model developments
- Operate AI agent platform
- Operate LLM gateway
- Perform fine-tuning
- Provision LLM endpoints in cloud and local environments
- Run systematic testing for RAG quality
- Select and configure LLM endpoints
- Set up CI CD and deployments
- Support AI use case assessments
- Support license and contract topics
- Track costs and token usage
- Version prompts and configurations
Perks/Benefits
- Flexible working hours
- Hybrid work
- Language courses
- Onboarding
- Onsite and Remote Events
- Seminars Coaching
- Sports programs
- State-of-the-art equipment
Skills/Tech-stack
API Integration | AWS | AWS Bedrock | Access Control | Authentication | Azure | Azure OpenAI | CI/CD | Data Privacy | Docker | Embeddings | Faiss | Fine Tuning | Incident Management | Information security | Kubernetes | LLMOps | Language Models | Large Language Models | Logging | Monitoring | Observability | Prompt engineering | Python | Qdrant | RAG | REST | Single Sign-On | Vector Databases | Vulnerability Protection | Weaviate
Education
Roles
AI | AI Infrastructure Engineer | Engineer | Infrastructure Engineer | LLM Engineer
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