AI Engineer
Tasks
- Automate evaluations for AI systems
- Benchmark models for quality and latency
- Build MCP servers and data serving layers
- Build and integrate production APIs
- Develop and optimize RAG systems
- Expose AI capabilities through APIs
- Implement end-to-end AI solutions
- Maintain code quality with tests and reviews
- Measure agent performance with LLMOps
- Monitor application health and performance
Perks/Benefits
- E-learning platform
- English learning support
- Equipment provided
- Extra day off
- Group insurance
- Private medical care
- Remote work
- Training budget
- Wellbeing platform
- Workshops and private therapy sessions
Skills/Tech-stack
Agentic Workflows | BM25 | GRPC | Grafana | Hybrid search | LLM orchestration | LLMOps | Langchain | Langfuse | Langgraph | Language Models | Large Language Models | Linters | MCP | MLOps | MLflow | Model Context Protocol | PGVector | PostgreSQL | Prometheus | Python | RAG | REST API | Retrieval-Augmented Generation | Semantic Search | Type Checking | Unit Testing | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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