Team Lead AI Engineering (w/m/d)
Tasks
- Build LLMOps and MLOps pipelines
- Coach and mentor engineers
- Conduct technical discovery feasibility analysis and risk assessment
- Define solution design and architecture
- Deliver end-to-end AI solutions
- Ensure performance security compliance data privacy and responsible AI
- Establish AI and LLM best practices
- Implement CI CD automated evaluation monitoring and versioning
- Integrate AI components into enterprise systems
- Lead AI engineering team
- Make architecture decisions for LLM systems
- Moderate architecture workshops and advise stakeholders
- Translate business requirements to scalable secure AI systems
Perks/Benefits
- Central office location
- Company laptop
- Company mobile phone
- Employee events
- Free drinks fruit and yogurt
- Mentoring program
- Mobility offers
- Retreats
- Sports offers
- Work-life balance
Skills/Tech-stack
APIs | Agent systems | Amazon Web Services | Artificial Intelligence | Backend Development | By Design | C# | CI/CD | Cloud Architecture | Cloud platform | Containerization | Context engineering | Cost Optimization | DevOps | Distributed Systems | Embeddings | Evaluation | Event Driven | Event-driven architecture | Generative AI | Google Cloud | Google Cloud Platform | Governance | Guardrails | Infrastructure as Code | Java | LLMOps | Langchain | Language Models | Large Language Models | Llamaindex | MLOps | Microservices | Microsoft Azure | Monitoring | Multi-Agent | Multi-Agent Systems | Observability | Prompt engineering | Python | RAG | Security by design | Semantic Kernel | Tool-Calling | TypeScript | Vector Databases | Web Services | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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