RAG Engineer
Tasks
- Build ingestion indexing retrieval pipelines
- Design RAG solutions
- Develop APIs and services
- Develop enterprise knowledge repositories
- Evaluate retrieval frameworks
- Implement governance and data security controls
- Implement semantic search
- Integrate retrieval with large language models
- Manage vector databases
- Monitor retrieval accuracy and performance
- Optimize latency scalability
- Optimize retrieval performance
- Recommend retrieval optimization enhancements
- Research knowledge management approaches
- Troubleshoot retrieval indexing issues
- Tune and evaluate retrieval quality
Perks/Benefits
- N/A
Skills/Tech-stack
API Development | AWS | Agile | Azure | Cloud Native | Cloud platform | Docker | Document ingestion | Embeddings | Generative AI | Google Cloud | Google Cloud Platform | Indexing | Information Retrieval | Kubernetes | Language Models | Large Language Models | Latency optimization | MLOps | Microservices | Python | Retrieval-Augmented Generation | Scalability | Semantic Search | Vector Databases | Vectorization
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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